Does china income FSDs follow Benford? A comparison between Chinese income first significant digit distribution with Benford distribution

Since Benford’s law is an empirical phenomenon that occurs in a range of data sets, this raises the question as to whether or not the same thing might be true in terms of the Chinese income distribution data. We focus on the first significant digit (FSD) distribution of Chinese micro income data from the 2005 Inter-Census sample, which corresponds to 1% of Chinese population and other micro income data from the China family panel studies (CFPS) and Chinese General Social Survey (CGSS). We use information theoretic-entropy based methods to investigate the degree to which Benford’s FSD law is consistent with the FSD of Chinese income data and our findings suggest consistency between the Chinese FSD income distribution and Benford’s distribution. The close connection between the two distributions has implications for the quality of the sample of Chinese micro data.     

跳频信号的归一化多普勒频差最大似然估计

针对双站定位涉及的跳频信号多普勒频差估计问题，提出了归一化的频差最大似然估计算法，利用两个定位站接收到的跳频脉冲串信号，构建一个关于基准跳频频率多普勒频差的似然函数，通过网格搜索得到使似然函数最大的多普勒频差估计，既解决了跳频信号在不同跳频频率上多普勒频差不一致的问题，又充分利用在不同频率的脉冲串信号提高了多普勒频差估计精度。通过仿真对算法的性能进行了评估，结果表明，与基于子空间的算法比较，在脉冲数达到240个时，所提算法执行效率提升30%以上。     

广义空间调制系统的正则化OMP检测算法

在广义空间调制（GSM）系统中，最大似然（ML）检测可以取得最优的检测性能，然而其计算复杂度随激活天线数的增加急剧增长。针对这一问题，提出了一种基于稀疏重构理论的低复杂度检测算法——正则化正交匹配追踪（ROMP）算法。该算法首先根据信道矩阵和当前残差的内积选取多个候选激活天线索引，接着对候选天线索引按正则化标准进行可靠性验证，剔除错误索引，缩小信号的搜索空间，最后通过求解最小二乘问题估计信号。仿真结果表明，与经典的正交匹配追踪（OMP）算法相比，所提算法以少许复杂度的增加为代价极大提升了检测性能，能够在检测性能与复杂度之间取得更好的折中。     

Consistent inference in fixed-effects stochastic frontier models

The classical stochastic frontier panel data models provide no mechanism to disentangle individual time invariant unobserved heterogeneity from inefficiency. Greene (2005a, b) proposed the so-called “true” fixed-effects specification that distinguishes these two latent components. However, due to the incidental parameters problem, his maximum likelihood estimator may lead to biased variance estimates. We propose two alternative estimators that achieve consistency for $n\to \infty$ with fixed $T$. Furthermore, we extend the Chen et al. (2014) results providing a feasible estimator when the inefficiency is heteroskedastic and follows a first-order autoregressive process. We investigate the behavior of the proposed estimators through Monte Carlo simulations showing good finite sample properties, especially in small samples. An application to hospitals’ technical efficiency illustrates the usefulness of the new approach.     

Distribution of residual autocorrelations for multiplicative seasonal ARMA models with uncorrelated but nonindependent error terms

In this paper, we consider portmanteau tests for testing the adequacy of multiplicative seasonal autoregressive moving‐average models under the assumption that the errors are uncorrelated but not necessarily independent. We relax the standard independence assumption on the error terms in order to extend the range of applications of the seasonal autoregressive moving‐average models. We study the asymptotic distributions of residual and normalized residual empirical autocovariances and autocorrelations under weak assumptions on noise. We establish the asymptotic behavior of the proposed statistics. A set of Monte Carlo experiments and an application to monthly mean total sunspot number are presented.     

Euro area real-time density forecasting with financial or labor market frictions

We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets and Wouters model, and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a measure of the external finance premium. The second allows for the extensive labor-market margin and adds the unemployment rate to the observables. The main question that we address is whether these extensions improve the density forecasts of real GDP and inflation and their joint forecasts up to an eight-quarter horizon. We find that adding financial frictions leads to a deterioration in the forecasts, with the exception of longer-term inflation forecasts and the period around the Great Recession. The labor market extension improves the medium- to longer-term real GDP growth and shorter- to medium-term inflation forecasts weakly compared with the benchmark model.     

Inference for large financial systems

We treat the parameter estimation problem for mean‐field models of large interacting financial systems such as the banking system and a pool of assets held by an institution or backing a security. We develop an asymptotic inference approach that addresses the scale and complexity of such systems. Harnessing the weak convergence results developed for mean‐field financial systems in the literature, we construct an approximate likelihood for large systems. The approximate likelihood has a conditionally Gaussian structure, enabling us to design an efficient numerical method for its evaluation. We provide a representation of the corresponding approximate estimator in terms of a weighted least‐squares estimator, and use it to analyze the large‐system and large‐sample behavior of the estimator. Numerical results for a mean‐field model of systemic financial risk highlight the efficiency and accuracy of our estimator.     

Estimating the gravity model when zero trade flows are frequent and economically determined

ABSTRACT

Since the 1950s, we have known that the presence of zero-valued dependent variables can seriously bias econometric estimates whether the zeros are included or excluded. Yet the widely-used gravity model is frequently estimated on samples that include large fractions of zeros. An influential paper by Santos Silva and Tenreyro – based on simulations that include no economically-determined zeros – concludes that the bias problems resulting from zeros and those resulting from heteroscedasticity and nonlinearity can be solved using the Poisson Pseudo-Maximum-Likelihood (PPML) model including the zero values. This paper begins by adapting the Santos Silva and Tenreyro experimental design to include economically-determined zeros to see whether this conclusion continues to hold. With this design, it finds that alternative estimators have lower bias than PPML. Changing to a Monte Carlo design that replicates the much-higher real-world frequency of predicted values near zero restores the finding of lower bias with the PPML estimator. The results highlight the need for very careful design of Monte Carlo experiments when evaluating alternative estimators of the gravity model.     

Effectiveness of harvest strategies in achieving multiple management objectives in a multispecies fishery

Fisheries management is characterised by multiple objectives, some of which may be complementary, while others may require trade‐offs between outcomes. Balancing these objectives is made more complex in the case of multispecies and multigear fisheries. In this paper, we develop a bioeconomic model that captures the key elements of such a fishery to test a range of potential harvest strategies to provide insights into how economic target reference points could lead to both desirable and undesirable management outcomes (e.g. discards). The model is developed as a long‐run optimisation model to identify target reference points to achieve multispecies maximum economic yield, and a dynamic recursive optimisation model, which includes more realistic representation of fishers’ behaviour, such as discards and trading of under‐caught species quotas. The potential economic, social and ecological impacts are evaluated using data envelopment analysis (DEA). The results suggest that the use of proxy target reference points can result in short‐term economic benefits at the cost of slower stock recovery and higher discarding. Limiting the number of species subject to quota controls may also prove beneficial in multispecies fisheries, while ensuring quota markets are efficient is likely to produce benefits irrespective of the harvest strategy adopted.     

Celebrity endorsements: Investigating the interactive effects of internalization,identification and product type on consumers’ attitudes and intentions

In line with Kang and Herr's work (2006), this research questions the ELM's contention that celebrity credibility serves foremost as a peripheral element in a persuasive communication context. Nevertheless, in a different light to the Kang and Herr's ‘either-central-or-peripheral-role’ of a source characteristic, this research advances that celebrity credibility plays concomitantly central and peripheral roles in a persuasive message context depending on product involvement and brand-purchase motive. Particularly, this research uses the notions of ‘source internalization’ and ‘source identification’ (Kelman, 1961) to theorize that source credibility can have a concomitant dual role (peripheral and central) in a persuasion context. More precisely, this research investigates the interactive effects of source identification and internalization with product involvement as well as brand-purchase motives on consumers' attitudes and intentions. Source internalization is predicted to have persuasive effects in the contexts of high-involvement as well as informational products. Source identification is predicted to have persuasive effects in the context of low-involvement as well as transformational products. The findings of two experiments show that celebrity credibility acts through only a single route (i.e., only internalization has persuasive effects) uniformly across different product involvement levels and brand-purchase motive types. We interpret these results with the lens of the ‘match-up’ hypothesis (Kamins, 1990).