省域全要素生产率地区差异的动态演进

笔者在运用索洛余值法对我国各地区全要素生产率进行估算的基础上,利用非参数的核密度函数法和马尔可夫链法对全要素生产率地区差异的动态演进进行了分析。研究结果表明,我国各地区全要素生产率差异较大,从东部往西部呈现逐渐降低的梯度分布格局;各地区之间全要素生产率的绝对差距在20世纪80年代呈现缩小趋势,而从1990年以后呈现加速扩大趋势;同时,核密度函数分布呈现双峰收敛趋势,进一步表明全要素生产率两极分化现象严重;从马尔可夫链的稳态分布来看,各地区的全要素生产率将继续保持较大差异,短期内难以实现均衡发展。     

Moral hazard and subsidized crop insurance

Along with adverse selection, moral hazard is one of the major hurdles that private and public insurance plans must contend with. Moral hazard occurs if risks are endogenous to a producer's behavior and if the insurer is unable to properly monitor the insured. We review the role of moral hazard in the US crop insurance program. We conduct an empirical analysis of one important aspect of the US crop insurance program—prevented planting. This provision provides indemnity payments if conditions are not suitable for planting. The program has been the subject of considerable controversy, especially during 2019, when the rate of claims is expected to be especially high. Because loss adjustors may encounter difficulties in assessing the weather conditions associated with prevented planting claims, the program is susceptible to moral hazard. We consider the extent to which prevented planting claims may be endogenous to prices. We find significant evidence of moral hazard. The likelihood of prevented planting claims increases as the expected market price decreases or as fertilizer costs increase for corn and soybeans in the Prairie Pothole Region and for grain sorghum and cotton in all states.     

Returns to women’s education using optimal IV selection

This paper investigates returns to women’s education by applying an optimal IV selection approach, post-Lasso IV estimation, which improves the first-stage predictive relationship between an endogenous regressor and instruments. Using the 2010 American Community Survey, we find that an extra year of education increases married women’s own income by $4,480 and spouse income by $8,822. Our findings indicate that 53% of the increase in women’s consumption by education is attributed to the marriage market, and thus, we conclude that the marriage market is the primary channel through which education improves women’s well-being. The results demonstrate the advantages of the post-Lasso approach: The resulting two-stage least squares estimator maintains efficiency without increasing finite sample bias and is less subject to the inconsistency problem when some instruments are invalid; This differs from the results using the instrument of birth quarters only, which is mostly applied in studies on returns to education.     

Nonlinearities in the real exchange rates: new evidence from developed and developing countries

This paper investigates nonlinearities in the dynamics of real exchange rates. We use Monte Carlo simulations to establish the size properties of the Teräsvirta-Anderson test, when the dynamics of the real exchange rate is influenced by an exogenous process. In addition, we show that a modified nonlinearity test, which includes additional right-hand-side variables, performs much better than the original in both Monte Carlo exercises and in the actual data on 1431 bilateral real exchange rate series. Finally, we investigate the dynamics of the real exchange rate for both developed and developing countries using the modified test for the recent floating period. In general, the results find a greater incidence of nonlinear dynamics for developing country real exchange rates.     

Sequential point estimation of normal mean under LINEX loss function

A sequential point estimation of the mean of a normal distribution is considered under LINEX loss function. The regret of sequential procedures are obtained. Furthermore, it is shown that a sequential procedure with the sample mean as an estimate is asymptotically inadmissible. An accerelated stopping time is also considered. Received: December 1999     

A note on the Robust Trend and ARARMA methodologies used in the M3 Competition

This brief note describes two of the forecasting methods used in the M3 Competition, Robust Trend and ARARMA. The origins of these methods are very different. Robust Trend was introduced to model the special features of some telecommunications time series. It was subsequently found to be competitive with Holt’s linear model for the more varied set of time series used in the M1 Competition. The ARARMA methodology was proposed by Parzen as a general time series modelling procedure, and can be thought of as an alternative to the ARIMA methodology of Box and Jenkins. This method was used in the M1 Competition and achieved the lowest mean absolute percentage error for longer forecasting horizons. These methods will be described in more detail and some comments on their use in the M3 Competition conclude this note.     

Estimating structural equation models with non-normal variables by using transformations

We discuss structural equation models for non-normal variables. In this situation the maximum likelihood and the generalized least-squares estimates of the model parameters can give incorrect estimates of the standard errors and the associated goodness-of-fit chi-squared statistics. If the sample size is not large, for instance smaller than about 1000, asymptotic distribution-free estimation methods are also not applicable. This paper assumes that the observed variables are transformed to normally distributed variables. The non-normally distributed variables are transformed with a Box–Cox function. Estimation of the model parameters and the transformation parameters is done by the maximum likelihood method. Furthermore, the test statistics (i.e. standard deviations) of these parameters are derived. This makes it possible to show the importance of the transformations. Finally, an empirical example is presented.     

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。     

叠加共轭对称训练序列的OFDM系统时频同步方法

针对正交频分复用（OFDM）系统对同步错误率和频率偏移敏感的问题,提出了一种叠加共轭对称训练序列的OFDM系统时间和频率同步方法。该同步方法将快速傅里叶逆变换（IFFT）调制后的序列构成具有共轭对称特性的训练序列,并叠加到OFDM数据符号上;在接收端,利用叠加训练序列和融合循环前缀信息来获取OFDM系统同步信息。理论分析和仿真表明：在信噪比为5 dB时,该同步算法定时同步正确概率已接近100%;在信噪比为4 dB时,频偏估计精度可以达到10-4;该同步算法不仅具有更好的同步性能,而且节省系统的有效带宽以及降低系统的计算法复杂度。     

鸟类目标微多普勒分析及参数估计

鸟类扑动的翅膀产生的微多普勒包含了目标的尺寸与微动特征信息,可用于鸟类目标参数估计,对探鸟雷达目标识别具有重要意义。首先建立鸟类目标雷达回波模型,推导了鸟翅膀散射点的微多普勒数学表达式,并通过计算回波的自相关函数估计目标扑翼频率;然后对微多普勒表达式进行泰勒级数展开,利用展开系数与扑翼幅度之间的关系得到扑翼幅度的估计值;最后根据半翼展与微多普勒谱宽之间的关系得到半翼展的估计值。仿真实验证明了所提方法的有效性和抗噪性：对扑翼幅度大于30??、半翼展大于0.3 m的目标,在信噪比高于0 dB的噪声环境下估计精度高。