Estimating exchange rate dynamics with diffusion processes: an application to Greek EMU data

Recently various exchange rate models capturing the dynamics during the transition from an exchange rate arrangement of floating rates into a currency union have been derived. Technically, these stochastic equilibrium models are diffusion processes which have to be estimated by discretely sampled observations. Using daily exchange rate data prior to the Greek EMU-entrance on 1 January 2001, we develop a rigorous estimation procedure. Our estimates point to an increasing interventionist economic policy in the run-up to the Greek EMU entrance. A comparison of this econometric indication with policy information provided (ex-post) by the Bank of Greece (BoG) in its Annual Report 2000 reveals that the BoG indeed pursued such an active policy stance (so-called institutional frontloading strategies).      

Can negative interest rates really affect option pricing? Empirical evidence from an explicitly solvable stochastic volatility model

The profound financial crisis generated by the collapse of Lehman Brothers and the European sovereign debt crisis in 2011 have caused negative values of government bond yields both in the USA and in the EURO area. This paper investigates whether the use of models which allow for negative interest rates can improve option pricing and implied volatility forecasting. This is done with special attention to foreign exchange and index options. To this end, we carried out an empirical analysis on the prices of call and put options on the US S&P 500 index and Eurodollar futures using a generalization of the Heston model in the stochastic interest rate framework. Specifically, the dynamics of the option’s underlying asset is described by two factors: a stochastic variance and a stochastic interest rate. The volatility is not allowed to be negative, but the interest rate is. Explicit formulas for the transition probability density function and moments are derived. These formulas are used to estimate the model parameters efficiently. Three empirical analyses are illustrated. The first two show that the use of models which allow for negative interest rates can efficiently reproduce implied volatility and forecast option prices (i.e. S&P index and foreign exchange options). The last studies how the US three-month government bond yield affects the US S&P 500 index.     

参与电商会促进猕猴桃种植户绿色生产技术采纳吗?——基于倾向得分匹配的反事实估计

本文利用陕西、四川两省686户猕猴桃种植户的调查数据,在采用变异系数法度量猕猴桃种植户绿色生产技术采纳程度的基础上,利用倾向得分匹配法构建反事实框架,实证分析参与电商对猕猴桃种植户绿色生产技术采纳的影响效应。结果表明:猕猴桃种植户绿色生产子技术的重要性依次为测土配方施肥技术、物理防治技术、套袋技术、无公害农药使用技术、有机肥施用技术;在控制样本选择偏差后,参与电商对猕猴桃种植户绿色生产技术采纳有显著的正向影响;参与电商对不同资本禀赋的猕猴桃种植户绿色生产技术采纳的促进效应存在差异;参与电商通过提升产品价格预期、提升经济收益水平、提升信息获取能力、追求正向社会评价四条路径来影响猕猴桃种植户的绿色生产技术采纳。     

微观企业全要素生产率测度方法的比较与应用

微观企业TFP通常是不可观测的,它的估计面临内生性、联立性等诸多问题。在系统分析微观生产函数估计所面临主要问题的基础上,经过蒙特卡洛模拟法,比较了微观生产函数最新估计方法的优劣,发现广泛应用的OP、LP和ACF参数估计方法,倾向于高估微观企业的TFP,而De Loecker、GNR和联合估计的TFP测度方法能够得到TFP的稳健估计,增加值类生产函数估计倾向于高估微观企业的TFP,并且高估TFP的离散程度。将前沿TFP测度方法用于中国生产要素错误配置问题的研究,发现要素再配置具有显著的TFP促进效应,但是低于Hsieh和Klenow(2009)政策模拟的估计结果。据此,提出以微观企业TFP开展实证研究的对策建议。     

中国工业部门要素分配份额决定因素研究

本文讨论我国工业部门要素分配份额的决定因素问题。在标准的新古典要素分配份额模型中,本文引入Dixit-Stiglitz垄断竞争以及企业目标函数的差异,建立了要素分配份额的决定模型。根据这个理论模型,本文建立了中国工业部门要素分配份额的计量模型,并利用系统GMM方法进行估计。回归结果表明,垄断能力越高,资本收入份额越高,国有和非国有企业的资本收入份额存在明显差异,国有企业的资本收入份额明显低于非国有企业,各类经济性质企业的资本收入份额从高到低依次为外商投资企业、港澳台企业、法人投资企业、集体企业、私有企业和国有企业。传统新古典分配模型考虑的技术因素,包括要素投入比的变化和技术进步,对要素分配份额的变化没有显著影响,表明我国工业部门要素替代弹性为1,因而劳动与资本相对价格的变化对要素分配份额没有显著影响。我们的结论是,工业部门要素分配份额变化的主要原因是产品市场垄断增加和国有部门改制引起的劳动力市场环境改变。     

关于状态空间方法中超参数估计的札记

章对状态空间方法中超参数估计的基本思想进行了论述,并对一般献中未详细证明的部分给出了证明,便于从事实际工作的统计工作和自学领会和掌握该模型。     

金融发展影响能源消费结构吗?——跨国经验分析

金融发展经常被认为是经济增长的一个重要推动因素.同样的,金融发展也可能会影响能源需求.金融发展可以通过促进金融系统发展、带动经济增长并促进产业结构调整这样的传导途径,使能源消费结构发生变动.本文对全球55 个国家23 年(1985～2007)的面板数据库的研究发现,金融发展的确会影响能源消费与需求,进而影响能源消费结构的变动.实证结果表明,金融发展会促进"化石燃料"能源和替代能源消费的增加,减少可再生能源的消费,对能源消费结构的改善有着一定的促进作用.所以,在制定能源相关政策和对高能耗部门进行产业调整时,要考虑金融发展的影响.     

Pursuing efficiency: a data envelopment analysis of MFIs in Latin America

This article analyses the overall profitability efficiency (PE) of Microfinance Institutions (MFIs) in Latin America. The PE of each MFI in the study is broken down into two components: pure technical efficiency and scale efficiency. One data envelopment model is used to analyse each component. Each MFI was labelled as either a bank, cooperative and credit union, nonbanking financial institution or non-governmental organization, and then the analysis was performed on each separate group. The results suggest that, on average, banks are the most efficient MFIs; while NGOs are, on average, the least efficient MFIs. On average, all 4 groups are more pure technically efficient than scale efficient. Banks, nongovernmental organizations, nonbanking financial institutions, cooperatives and credit unions all seem to have problems with scale efficiency. Many MFIs seem to be operating on the increasing returns to scale frontier and are in a more favourable position for expansion.     

我国省级区域金融发展对经常项目的影响研究——基于货物贸易视角的分析

本文选取我国大陆31个省(市、自治区)2007年-2018年的面板数据,综合运用系统GMM和差分GMM估计方法,实证检验了沿海与内陆、沿边与非沿边、享受优惠政策高与低、金融控制强与弱等4类不同省区金融发展对经常项目余额的影响。研究结果表明:使用全部样本估计时,金融发展显著负向影响经常项目余额,这一结论经稳健性检验后依然成立。使用不同区域的子样本估计时,金融发展对沿海省区、非沿边省区、享受优惠政策高以及金融控制弱省区的经常项目余额的抑制作用较大,而在其他省区作用较小。因此,各地区应充分利用金融手段来调整进出口余额,以保证经常项目的持续平衡。     

Combining the minimum-variance and equally-weighted portfolios: Can portfolio performance be improved?

It is documented in the literature that due to estimation errors, mean-variance efficient portfolios deliver no higher out-of-sample Sharpe ratios than does the naïve equally-weighted portfolio (EWP). This paper demonstrates how the out-of-sample performance of the minimum-variance portfolio (MVP) can be improved in the presence of estimation errors by combining the MVP and EWP. Our results indicate that an appropriate combination of the MVP and EWP can enhance Sharpe ratios under any scenarios considered, and can also reduce the portfolio risk if short-selling is allowed. However, the combination strategy is not able to generate a lower risk level than the MVP when a short-selling restriction is imposed. We find that the optimal combination coefficient depends on the factors that greatly impact estimation errors in the MVP, including sample size, estimation method, no-short-selling restriction, and length of the out-of-sample period under consideration.