Short Selling Pressure,Stock Price Behavior,and Management Forecast Precision: Evidence from a Natural Experiment

Using a natural experiment (Regulation SHO), we show that short selling pressure and consequent stock price behavior have a causal effect on managers’ voluntary disclosure choices. Specifically, we find that managers respond to a positive exogenous shock to short selling pressure and price sensitivity to bad news by reducing the precision of bad news forecasts. This finding on management forecasts appears to be generalizable to other corporate disclosures. In particular, we find that, in response to increased short selling pressure, managers also reduce the readability (or increase the fuzziness) of bad news annual reports. Overall, our results suggest that maintaining the current level of stock prices is an important consideration in managers’ strategic disclosure decisions.     

基于时间序列的山东省人均GDP分析与预测

人均国内生产总值综合考虑了一个地区经济总量和人口基数,能够较好地反映一个地区经济增长和居民经济生活水平。本文以1978—2013年的山东省人均GDP数据为样本,用时间序列分析方法建立自回归预测模型。根据预测,山东省“十二五”期间人均GDP呈现出先慢后快的增长特点,可能原因是前期受金融危机影响较大,后期影响逐渐减弱。政府应保持宏观经济政策连续性稳定性,不断扩大开放,实施创新驱动,加快转方式调结构促升级,深化国民收入分配体制改革,实现经济持续健康发展和社会和谐稳定。     

扬州市生态农业发展评价及预测研究

［目的］农业是国民经济的基础产业，发展生态农业是实现农业经济稳步增长的重要途径，也是我国发展现代农业的战略选择。对生态农业的现状进行评估，以期以此为依据为今后的发展提供可行性建议。［方法］文章研究从经济效益、社会效益和生态效益3个方面构建了包含14个指标在内的扬州市生态农业发展评价指标体系，并采用熵权法和加权法综合评定2011—2016年该市生态农业发展的经济效益、社会效益和生态效益及综合效益得分，在此基础上采用GM（1， 1）灰色模型对2018—2027年扬州市生态农业的发展程度进行了预测。［结果］2011—2016年扬州市生态农业发展的社会效益呈持续增长态势， 2011—2015年经济效益呈上升趋势， 2016年经济效益明显下降。生态效益分别在2012年和2016年出现两次波动。总体来看， 2012—2015年扬州市生态农业发展的综合效益逐年递增， 2016年由于经济效益的急剧降低，导致综合效益下降。2018—2027年该市生态农业的发展水平一直保持可持续状态，且发展度在逐年递增。［结论］扬州市在今后的发展过程中应注重转变生产方式，积极调整农业生产模式，努力实现农产品的集约化生产。注重环境保护，实现化肥农药使用量零增长，达到经济效益与社会效益和生态效益协调增长。     

The effects of analyst forecasts and earnings trends on perceptions of management forecast credibility

We examine whether analyst forecasts influence investors’ perceptions of the credibility of a good news management earnings forecast. We hypothesize that the effect of analyst forecasts will depend on whether the analyst forecast confirms management’s forecast and the extent to which management’s forecast is consistent with the prior earnings trend. Findings indicate that the positive effect of a confirming analyst forecast is greater when the management forecast is trend inconsistent than when it is trend consistent. The negative effect of a disconfirming analyst forecast does not differ based on management forecast trend consistency.     

Conditional Persistence of Earnings Components and Accounting Anomalies

We suggest that the failure of investors to distinguish between an earnings component's autocorrelation coefficient (unconditional persistence) and the marginal contribution of that component's persistence to the persistence of earnings (conditional persistence) provides a partial explanation of post‐earnings‐announcement drift, post‐revenue‐announcement drift, and the accrual anomaly. When the conditional persistence of revenue surprises is high (low) relative to its unconditional persistence, both the post‐earnings‐announcement drift and the post‐revenue‐announcement drift are high (low), because investors’ under‐reaction to revenues and earnings is stronger when the persistence of revenue surprises is more strongly associated with the persistence of earnings surprises. Also, the mispricing of accruals decreases substantially when the conditional persistence of accruals is high relative to its unconditional persistence, because investors’ over‐reaction to accruals is mitigated when the persistence of accruals is indeed more strongly associated with the persistence of earnings. Our findings also suggest that financial analysts’ failure to distinguish between unconditional and conditional persistence of revenues and accruals results in more biased revenue and earnings predictions.     

Forecasting China's GDP growth using dynamic factors and mixed-frequency data

Forecasting GDP growth is important and necessary for Chinese government to set GDP growth target. To fully and efficiently utilize macroeconomic and financial information, this paper attempts to forecast China's GDP growth using dynamic predictors and mixed-frequency data. The dynamic factor model is first applied to select dynamic predictors among large amount of monthly macroeconomic and daily financial data and then the mixed data sampling regression is applied to forecast quarterly GDP growth based on the selected monthly and daily predictors. Empirical results show that forecasts using dynamic predictors and mixed-frequency data have better accuracy comparing to traditional forecasting methods. Moreover, forecasts with leads and forecast combination can further improve forecast performance.     

大城市劳动力供需平衡与外来劳动力就业政策研究——以上海市为例

文章在经济转型和大城市人口调控背景下,研究了上海劳动力资源供需平衡趋势与外来劳动力需求情况。研究显示,在上海经济保持一定的增长速度下,2015-2020年外来劳动力需求量在700-856万人之间,这使大城市在对待外来劳动力上处于尴尬境地,一方面面临着经济发展对外来劳动力的依赖性,另一方面面临着大城市人口调控的压力。目前上海劳动力市场中外来劳动力与本地劳动力在就业岗位、工资待遇、社会福利等方面仍存在一定的差异。外来劳动力与本地劳动力在岗位上更多的是一种优势互补关系,对外来劳动力歧视有悖于社会公平理论,同时政府的强行调控政策也不利于劳动力市场的发展。政府的职责应该是尽可能地创造出健康、有序、公平的市场秩序,让市场在调节劳动力供需和结构性短缺上发挥决定性作用。     

平衡膳食模式视角下粮食需求预测

[目的]随着时代的进步和社会经济的发展,对粮食安全内涵的理解也在逐步深化,粮食安全内涵不仅包括数量方面,还包括营养健康安全,保障居民营养健康成为粮食安全的新时代内涵。基于营养目标的粮食需求研究,建立营养—消费—生产的粮食生产模式,对引导居民合理健康消费和保障粮食安全具有十分重要的意义。[方法]文章首先分析了我国城乡居民营养消费状况,然后基于平衡膳食模式视角,引入标准人消费系数这一概念对我国未来粮食需求进行了更准确的预测。[结果]城镇居民粮食消费已达到高营养目标,但目前农村居民仅达到低营养目标水平,相当于21世纪初的城镇消费水平;考虑人口结构因素,2020年和2030年粮食需求总量分别为4.8亿t和5.6亿t,比没有考虑人口结构变化时分别减少8700万t和2 600万t。[结论]根据分析结果,提出以下几点政策建议:(1)宣传普及营养健康消费知识,引导居民合理膳食;(2)关注人口结构变动,及时调整粮食安全调控机制;(3)优化食品工业的产业机构升级,提高饲料粮转化率。     

Forecasting turning points in tourism growth

Tourism demand exhibits growth cycles, and it is important to forecast turning points in these growth cycles to minimise risks to destination management. This study estimates logistic models of Hong Kong tourism demand, which are then used to generate both short- and long-term forecasts of tourism growth. The performance of the models is evaluated using the quadratic probability score and hit rates. The results show that the ways in which this information is used are crucial to the models’ predictive power. Further, we investigate whether combining probability forecasts can improve predictive accuracy, and find that combination approaches, especially nonlinear combination approaches, are sensitive to the quality of forecasts in the pool. In addition, model screening can improve forecasting performance.