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当前关于金融脆弱性的研究集中于国家这一宏观层面,对于省域金融脆弱性的研究还存在相当大的研究空间。正是基于这样一种相对创新性的视角,在对金融脆弱性现有研究进行综述的基础上对辽宁省的金融脆弱性的诱因进行了分析,并提出推动非银行金融机构的发展、拓展规模较大的银行的非利息收益以提升银行盈利能力以及全力清除不良贷款是应对辽宁省金融脆弱性的可行策略。 相似文献
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In 2015, Swiss voters had the opportunity to impose a tax on the super rich in a popular vote and thereby fund a redistributive policy. However, a large majority voted against its seemingly obvious self-interest and rejected the tax. We propose an explanation for this puzzling outcome, bridging the usually separate behavioralist and institutionalist perspectives on the politics of inequality. We start from the observation that political economy tends to neglect processes of preference formation. Theorising preferences as socially constructed, we show that interest groups played a major role in shaping the outcome of the vote. Business frames were multiplied through allied parties and the media and had a major impact on individual voting behaviour. In addition, we demonstrate that interest groups representing business interests derive the content of their communication from business’s structurally privileged position in the capitalist economy. Specifically, creating uncertainty about possible perverse effects of government policies on jobs and growth is a powerful tool to undermine popular support. Frames based on this structural power ultimately explain why the Swiss refrained from ‘soaking the rich.’ 相似文献
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Major changes are underway in the U.S. retail banking sector toward heavy investments in technology and fewer in personnel. Using the 2017 survey of household economics and decision‐making (SHED) (n = 11,359), we examine the relationship between saving behavior related to emergency, long‐term and periodic expenses and personal, technological, and hybrid bank account access methods. Binary logistic regression models were used to estimate the odds of reporting various saving behaviors in relation to various banking access methods. Findings suggest that the personal access method is positively associated with savings behavior for periodic expenses for the general population, and negatively associated with emergency savings in people with lower education attainment. Technology is associated with all types of saving behavior, while the hybrid access method is associated only with saving for periodic expenses. As investments in self‐service technology increase, the importance of access methods to savings behavior must be considered. 相似文献
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In this paper, we develop a multilayer network structure and reveal the relationship between network structure and systemic risk. Unlike many previous studies, our model considers both liability and cross-holding of shares between financial institutions simultaneously. We propose a new systemic risk measurement by exploring the dynamic mechanism of financial contagion in the multilayer network. We display the network structure of Chinese financial institutions, including connectivity and diversity, and identify the systemic importance of them. We demonstrate that the multilayer network plays a non-linear role in financial risk spreading. Using the panel regression model and several experiment evidences, we show that the systemic risk can be explained more effectively by the linkage diversity more than the connectivity at both the institutional level and the system level. Our results highlight the importance of considering contagion mechanisms that go beyond a simple single-layer network structure. 相似文献
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Systems’ thinking places high value on understanding the context. This study focused on the collection of disaggregated data in order to understand the context, to facilitate improvement of health outcomes. The aim of this article was to assess the implementation of municipal ward-based health data collection (disaggregated data) and health care workers’ perceptions of this data collection process. This cross-sectional study used mixed methods in Amajuba district. The participants were professional nurses at the Primary Health Care level. Of the 131 respondents, 123 (93.9%) collected municipal ward-based health data, and found it useful. Opportunities for improving data collection were identified. Disaggregation of the data at ward level contributes to a better understanding of the target population’s health, assists planning for health needs and enables provision of targeted interventions in order to improve health outcomes, to prevent financial regression and waste of health resources. 相似文献
8.
PITFALLS IN CROSS‐SECTION STUDIES WITH INTEGRATED REGRESSORS: A SURVEY AND NEW DEVELOPMENTS
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In cross‐section studies, if the dependent variable is I(0) but the regressor is I(1), the true slope must be zero in the resulting “unbalanced regression.” A spuriously significant relationship may be found in large cross‐sections, however, if the integrated regressor is related to a stationary variable that enters the DGP but is omitted from the regression. The solution is to search for the related stationary variable, in some cases the first difference of the integrated regressor, in other cases, a categorical variable that can take on limited number of values which depend on the integrated variable. We present an extensive survey, new developments, and applications particularly in finance. 相似文献
9.
中国的互联网金融经历了一个先创新发展后监管规制的过程,本文通过对网络借贷行业的实证研究,分析监管规则的出台实施对新型互联网融资市场有效性的影响。实证结果表明,网络借贷平台资金的银行存管、持有ICP证等强制性规定缓解了投资者、平台企业与借款人之间的信息不对称,对克服早期平台间通过竞相承诺高回报率来吸引投资者导致的“柠檬市场”问题、对解决网贷市场上缺乏平台风险性高低有效信号的问题都起到了正向作用,有助于互联网融资市场的有效性提高。 相似文献
10.
《International Journal of Forecasting》2019,35(1):80-99
This paper discusses the specifics of forecasting using factor-augmented predictive regressions under general loss functions. In line with the literature, we employ principal component analysis to extract factors from the set of predictors. In addition, we also extract information on the volatility of the series to be predicted, since the volatility is forecast-relevant under non-quadratic loss functions. We ensure asymptotic unbiasedness of the forecasts under the relevant loss by estimating the predictive regression through the minimization of the in-sample average loss. Finally, we select the most promising predictors for the series to be forecast by employing an information criterion that is tailored to the relevant loss. Using a large monthly data set for the US economy, we assess the proposed adjustments in a pseudo out-of-sample forecasting exercise for various variables. As expected, the use of estimation under the relevant loss is found to be effective. Using an additional volatility proxy as the predictor and conducting model selection that is tailored to the relevant loss function enhances the forecast performance significantly. 相似文献