Experts,firms, consumers or even hard data? Forecasting employment in Germany

In this article, we forecast employment growth for Germany with data for the period from November 2008 to November 2015. Hutter and Weber (2015) introduced an innovative unemployment indicator and evaluated the performance of several leading indicators, including the Ifo Employment Barometer (IEB), to predict unemployment changes. Since the IEB focuses on employment growth instead of unemployment developments, we mirror the study by Hutter and Weber (2015). It turns out that in our case, and in contrast to their article, the IEB outperforms their newly developed indicator. Additionally, consumers’ unemployment expectations and hard data such as new orders exhibit a high forecasting accuracy.     

The nonobserved economy in the European Union

To better understand the share of the nonobserved economy (NOE) in the European Union, especially on the PIIGS, we estimate, through the multiple indicators multiple causes model, the path between 1980 and 2013. The model includes (i) the tax burden (disaggregated into direct and indirect taxes), a proxy of regulation burden, the unemployment rate and self-employment as causes of the NOE economy; (ii) the GDP and the labour force participation ratio as indicators of the NOE economy. In particular, the estimated weight of NOE as a percentage of official GDP was always higher in the PIIGS group.     

Value at risk forecasting for volatility index

Forecasts of values at risk (VaRs) are made for volatility indices such as the VIX for the US S&P 500 index, the VKOSPI for the KOSPI (Korea Stock Price Index) and the OVX (oil volatility index) for crude oil funds, which is the first in the literature. In the forecasts, dominant features of the volatility indices are addressed: long memory, conditional heteroscedasticity, asymmetry and fat-tails. An out-of-sample comparison of the VaR forecasts is made in terms of violation probabilities, showing better performance of the proposed method than several competing methods which consider the features differently from ours. The proposed method is composed of heterogeneous autoregressive model for the mean, GARCH model for the volatility and skew-t distribution for the error.     

Real exchange rates: are they dominated by fundamental factors?

Using Bayesian model averaging, we determine which fundamental pair-wise differences suggested by the literature on optimum currency areas give the best explanation of medium-term variability of bilateral real exchange rates. The intercept in the best specification is statistically insignificant, implying that for a hypothetical pair of economies for which the differences were zero, the bilateral real exchange rate would not move. Thus, the ‘non-fundamental’ element of the medium-term real exchange rate variability is, in our sample at least, negligible on average. In other words, floating exchange rate does not in itself imply, on average, more real exchange rate variability in the medium term than an exchange rate peg.     

马来西亚华商的价值观、经营模式与社会义务

以杂货店为研究对象,研究马来西亚华商的价值观,探讨从清代以在马来西亚的传统华人杂货商,致富成功与企业价值观、经营模式的最初渊源,提炼出传统儒家价值观、忠、信、义对其成功致富的意义.     

中国再生资源价格长期波动特征及其对经济的影响研究

尽管再生资源在工业生产中替代原生资源的比例逐渐升高,但对再生资源价格波动的特征及对经济的影响尚缺乏研究。本文以再生铜为例,采用GRACH族模型分析发现,我国再生铜价格的波动存在一定集聚性和持续性,价格波动比较缓慢。且负向冲击对再生铜价格波动的影响比正向冲击大,存在显著的杠杆效应。此外,再生铜价波动具有显著的GARCH-M效应,即预期的风险对再生铜价格波动具有正向影响。然后采用VAR模型和脉冲响应函数等方法,引入产出、投资、消费和通货膨胀率变动等宏观经济变量,定量分析了再生资源价格波动与中国经济之间的关系。检验结果表明：再生铜价作为建筑业重要的生产资料,其价格上涨短期内 促使GDP增长,但长期则抑制投资,最终可能影响GDP增长并提高通货膨胀率,即再生铜价格上涨对国家经济发展有不利影响。本文的实证结果揭示出,对中国经济的影响而言,废旧金属价格的变动只是某种表象,经济增长和通货膨胀率变动的背后是更为复杂的原因,问题的实质是以固定投资拉动经济增长的发展模式和部分地区对房地产业过度依赖的产业结构的变化等对中国经济产生的根本性的影响。     

基于城市视角下新能源汽车产业技术创新效率评价

在能源和环境问题日益凸显的情况下,新能源汽车的发展无疑为我国汽车产业的发展提供了新 的契机。借鉴区域和产业技术创新效率评价研究范式,结合新能源汽车特点,论文有针对性 地选取评价指标,以11个新能源汽车主要推广城市创新数据为基础,在城市视角下应用主成 分分析与DEA的组合方法,定量评价了其技术创新效率。通过对投入产出数据的DEA有效性进 行对比分析,发现这11个城市的整体技术创新效率偏低,主要是受规模效率与纯技术效率交 叉作用影响,且普遍存在新产品开发投入冗余、研发支出投入过多、企业规模不合理和资源 利用效率不高等问题。最后根据分析结果进一步提出了对策建议。     

经济新常态下金融包容与产业结构转型——基于中国省级面板数据的分析

在经济新常态背景下,产业结构面临重大调整,金融包容的融入,使中小企业或个人能够获得价格合理、方便快捷的金融资源,扶持创业创新发展,形成新的增长动力。本文基于1995～2012年中国31个省市的相关数据,运用面板数据模型和分位数回归方法,深入探讨金融包容对产业结构转型的影响。结果表明,金融包容与产业结构转型具有显著的正向关系,并且在不同分位点上金融包容水平对产业结构转型表现出较强的解释力,随着产业结构向高级化发展,金融包容在产业结构转型升级中的作用逐步凸显。经济增长、教育发展、财政支出规模和城市化水平均对产业结构转型具有促进作用,而过多的物质资本投入不利于产业结构转型。     

基于百度指数的碳交易市场波动率的实证研究

碳交易市场波动率研究主要基于成交量数据对收益率GARCH效应的解释作用。在互联网时代可以有更新更为有效的方法来衡量碳交易市场的波动性。基于“碳交易”词条的百度指数,以湖北碳交易市场中的收益率为样本,本文通过对比使用引入成交量和搜索量的IGARCH（1,1）模型,实证研究发现传统的量价方程的确没有解释力,而百度指数可以对收益率的GARCH效应做出部分合理的解释,这可以在某种程度上反映湖北碳交易市场的交易信息流。     

灰色模型在股票价格预测中的应用——以中国石化为例

通过对原始数据进行筛选,将GM(1,1)模型用于股票预测,对交易日收盘价格进行预测,并以中国石化(600028)2012-01-04至2012-12-31的交易数据为例进行了分析。分析结果表明,灰色预测模型的平均预测准确度为98.63%。考虑到股票交易规则,42%的预测数据为有效预测,有效预测的平均预测准确度为99.31%。