Financial knowledge among Iranian investors

This research is the first to describe financial knowledge in the Islamic Republic of Iran. Data were collected from a convenience sample of investors in the Tehran Stock Exchange. The data were used to examine objective and subjective knowledge as well as overconfidence in one's financial knowledge. The results indicated that compared with other populations, Iranians did not perform well on either basic or advanced financial knowledge questions, especially when the questions dealt with interest rates. This is likely related to the Islamic law ban on usury‐based investing. Regression analysis indicated that demographic charactristics related to basic financial knowledge were income, labour force status and being a student. Demographic characteristics related to advanced financial knowledge were education, labour force status and age. Higher income and education reduced the odds of being overconfident about one's financial knowledge, while being a student and male increased the odds. The article concludes with recommendations about future research as well as building a national financial education strategy.     

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.     

Corrigendum to “Characterization of the asymptotic distribution of semiparametric M-estimators” [J. Econometrics 159 (2) (2010) 252–266]

This note provides correction to Ichimura and Lee (2010).     

Socio-demographics,political attitudes and informal sector employment: A cross-country analysis

In this paper, we empirically investigate the relationship between informal sector employment and micro-level socio-demographic characteristics, political acts and attitudes, and individual norms. Using self-reported individual micro-level data from the World Values Survey for seven developing countries (China, Ecuador, Egypt, Mexico, Peru, South Africa and Yemen), our cross-country regressions and principal component analysis reveal that socio-demographic characteristics of individuals are strong predictors of their informal sector employment. Our estimations further document that individual preferences for an economically strong, interventionist and egalitarian state and confidence in state and political institutions are positively and significantly correlated with informal sector employment, whereas variables associated with confidence in free market institutions and support for competition are negatively and significantly correlated with informal sector employment. We also show that individuals who participate either actively or inactively in peaceful and lawful political processes are significantly less likely to work in the informal sector. Finally, we document that individual norms, such as religiosity and tax morale, are negatively correlated with informal sector employment. Throughout our analysis, instead of having to rely on ad-hoc informality categorizations of third parties, we base our measurement of informal sector employment directly on the self-evaluation of individuals, who have the best information on the degree of their informality.     

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。     

利用信道状态信息的室内定位技术

多径效应导致基于信号接收强度（RSSI）的室内定位方法精度不高，采用更细粒度的物理层信道状态信息（CSI）可以区分不同路径，提高定位精度。在已有基于CSI室内定位方法的基础上，通过改进对数距离路径损耗模型，得到CSI与传输距离的关系，并结合目标位置所测得的CSI值回归出目标与发射端的距离，最后通过三边定位法预测出目标的位置坐标。实验表明，相比基于RSSI的定位方法以及已有的基于CSI的定位方法，所提方法2 m以内的误差概率提高了将近40%和20%，有效提高了定位精度。     

Multidimensional brand equity and asymmetric risk

The authors investigate the extent to which central customer-based brand equity dimensions (Differentiation, Relevance, Esteem, Knowledge, and Energy) influence a firm’s systematic risk (i.e., beta) during both market upturns and downturns. The results demonstrate that aggregating upside and downside beta or different dimensions of brand equity masks the true associations which can be seen only in the disaggregate analyses. The authors find that Relevance and Knowledge play roles as stabilizers, showing negative relationships with both upside gains and downside risk, while Esteem plays the role of protector, showing a negative relationship with only downside losses and not influencing upside gains; Energy acts as a booster, being positively associated with a firm’s potential gains in a period of market growth without increasing the firm’s expected losses during a bad market. The positive relationship of Energy with aggregate risk could be misleading as it hides the beneficial effect of Energy as a booster. The authors also find that Relevance is the most important consideration when people make choices in bad market situations, while Energy becomes the most crucial deciding factor in good market situations. Taking advantage of the multidimensional constructs of brand equity while allowing for the asymmetrical characteristics of risk enables managers to capture the differential role of each brand equity dimension in influencing firm risks, which leads to more sophisticated strategic decisions regarding risk management. In addition to general brand strategy, the authors provide tailored brand strategies to firms from different industries or with different financial characteristics.     

Selection of influential variables in ordinal data with preponderance of zeros

Presence of excess zero in ordinal data is pervasive in areas like medical and social sciences. Unfortunately, analysis of such kind of data has so far hardly been looked into, perhaps for the reason that the underlying model that fits such data, is not a generalized linear model. Obviously some methodological developments and intensive computations are required. The current investigation is concerned with the selection of variables in such models. In many occasions where the number of predictors is quite large and some of them are not useful, the maximum likelihood approach is not the automatic choice. As, apart from the messy calculations involved, this approach fails to provide efficient estimates of the underlying parameters. The proposed penalized approach includes ?₁ penalty (LASSO) and the mixture of ?₁ and ?₂ penalties (elastic net). We propose a coordinate descent algorithm to fit a wide class of ordinal regression models and select useful variables appearing in both the ordinal regression and the logistic regression based mixing component. A rigorous discussion on the selection of predictors has been made through a simulation study. The proposed method is illustrated by analyzing the severity of driver injury from Michigan upper peninsula road accidents.     

Ideological taboos,entry barriers,and FDI attraction: Evidence from China

Developing and transitional countries often impose a wide variety of entry barriers on foreign direct investments (FDIs). One important reason behind these entry barriers is ideological taboos. However, do these taboos actually affect the inflow of FDIs? With the help of China’s “cultural system reform,” this study uses a panel data of 283 prefecture-level cities in China for 1994–2017 and the difference-in-differences method to evaluate the effect of the cultural system reform on regional FDI. We found that the cultural system reform remarkably promoted the inflow of FDIs by deregulating institutions and removing entry barriers, and the attraction of FDI has slowly increased along with the deepening of the reform. Our conclusions still hold after performing several robustness tests, thereby highlighting ideologies as important barriers to the inflow of FDIs into less developed countries.