中国分行业资本存量估算：1990~2014年

通过借鉴中国资本存量已有研究文献的成果,以细分行业差别化的折旧率估算为基础,通过分析投资结构和折旧率的关系,估算出第二、第三产业和总量的时变折旧率,系统地估算出1990~2014年总量、三次产业和细分行业的资本存量。估算结果及分析表明:由于投资结构的变化,总量、第三产业折旧率呈下降趋势,第二产业折旧率呈先上升再下降趋势;目前在我国,“过度投资”和“投资不足”并存,且“过度投资”的是资本效率比较低的行业,“投资不足”的是资本效率比较高的行业。解决“投资不足”问题的关键是打破行业垄断,尤其是行政垄断,引入市场竞争机制。     

基于十大分类的中国资本存量重估：1978~2016年

研究目标：根据最新的统计数据测算我国的资本存量。研究方法：根据我国1978~2016年的相关数据,利用永续盘存法进行测算。研究发现：本文的测算的资本存量要略小于现有文献的结果;我国的资本产出比正处于快速上升阶段。研究创新：使用最新统计数据将资本构成进一步细化为十个大类,分别考虑了每类资本的初始资本存量、折旧率、资本形成额和价格指数,计算得到1978~2016年各类资本存量;在应用几何折旧法时,将折旧率拆解为固定折旧率与可变折旧率两部分,其中可变折旧率与经济增长率正相关,更加贴近实际情况。研究价值：在对已有研究进行深入分析的基础上,采用更为精细的方法和更贴近现实的假设,应用最新的数据,重新估算中国资本存量,得出的研究结果相比过去的研究更加可靠。研究结果对今后的基础研究具有重要借鉴意义。     

中国资本存量K的再估算：1952～2006年

本文通过比较现有资本存量的研究文献吸取了有益的内容,同时扬弃了部分不合理的估算假定和前后不一致的推算方法,重新构建了资本存量估算中的四个核心指标,尤其是对基期资本存量和折旧率的确定进行了细致的推算。本文还根据国家统计局最近基于经济普查和年度修正的最新数据资料,利用永续盘存法估算了1952～2006年全国和省际的资本存量,从而为后续的许多相关研究提供了更为准确的基础数据。     

我国服务业资本存量地区差异及其成因——基于空间经济学的实证分析

资本存量对经济增长具有特别意义,因此服务业资本存量的估算工作受到了广泛关注。但由于受估算数据的制约,鲜有第三产业资本存量估算的文献。本文运用PLA方法对分地区的第三产业资本存量进行了估算,并采用Moran指数测算了第三产业资本存量空间分布机理。研究发现:自1978年以来我国服务业资本存量增长迅速,但分布不均衡且呈现明显的空间集聚特点。     

省际第三产业资本存量：框架、检验及动态轨迹

研究目标：省际第三产业资本存量的估算、检验及动态轨迹分析。研究方法：运用永续盘存法非传统途径估算总资本存量K、净资本存量Kn、生产性资本存量KP，采用重心法考察第三产业资本存量的空间分布特征。研究发现：K、Kn是反映资产价格财富的价值指标，KP是反映资产生产能力和服务效率的物量指标。相较K、Kn，使用KP作为资本投入指标，能反映固定资产的生产能力和资本投入状况。自1978年以来，我国第三产业资本投入持续增长且呈现以东部为核心的态势，资本分布的区域不均衡状况没有根本改变。研究创新：从理论内涵和估算方法上比较分析K、Kn、KP三者并进行检验。研究价值：有助于中国第三产业资本估算与国际接轨、成为国际核算案例的一部分并更好地参与讨论。     

中国资本存量的度量、空间演化及贡献度分析

本文首先采用永续盘存法对我国各省份资本存量进行了估算。基于估算结果,分析了资本重心的空间移动轨迹,发现轨迹以1991年和2003年为转折点分成了三个阶段。为分析资本重心迁移的主导因素,本文发现第一阶段重心持续向东北方向移动的主要原因是东部的资本快速积累。第二阶段重心向东南方向移动是由东部地区仍然保持快速积累和西部地区积累滞后引起的。第三阶段重心向北方移动是西部地区积累滞后和东北地区快速积累所致。最后,分析资本重心迁移与经济重心迁移相背离的原因是资本存量不是影响经济增长的唯一变量,它的变动不一定会带动经济同步变动。     

中国研发（R&D）资本存量估计：1978—2012

目前鲜有文献涉及R&D资本存量的估计,且存在明显缺陷,以致影响了后续研究的准确性和可靠性,因而有必要延长年限重新估计。本文合理选取R&D投入指标、增长率g、折旧率δ和价格指数权重,利用永续盘存法对中国1978—2012年R&D资本存量进行了测算。研究发现:(1)2000年是中国R&D资本存量增长的突破点,实现了从缓慢低位增长到迅速攀升的转变;(2)R&D资本存量占GDP份额呈现为"U"型走势,经历了先下降后提升的过程;(3)无论是R&D资本存量的绝对值还是R&D资本存量占GDP份额,中国均明显落后于美国。中国R&D活动取得了重要进展,但仍需通过加大R&D投入以提升国家创新能力。     

中国经济增长中的公共资本外溢

本文估算了中国1952-2010年的水利基础设施的物质资本存量,并在基于政府生产性支出的内生增长框架中估计水利资本的产出效率,证实公共资本具有显著的外溢效应。在此基础上,本文着重揭示,在基于历史数据的中国经济增长研究中,不仅水利等基础设施公共资本存量存在明显的测量误差,而且总的资本存量、劳动投入等生产要素的基础数据,也可能存在严重的准确性问题,影响了对经济增长的准确判断,急需系统深入的研究讨论加以完善以形成理论共识。     

中国R&D资本存量测算：1952~2014年

2008年SNA修订了R&D支出的核算方法,R&D支出不再视为中间消耗,而是作为固定资本形成处理。本文依据2008年SNA和我国R&D统计调查数据等,科学测算了1952年以来每年R&D活动所形成的资产价值,同时对R&D资产进口和出口进行了适当调整。然后,在合理选取和估计R&D资产折旧率、R&D价格指数和基年R&D资本存量的基础上,根据永续盘存法对我国1952~2014年R&D资本存量进行了测算。结果显示,我国R&D投资与R&D内部经费支出的年平均比例为95.5%,我国R&D资本存量总体上呈快速增长趋势,2014年达到42244亿元,且R&D资本存量与GDP之比呈“N”形趋势,经历了先上升后下降再上升的过程。     

结构变动、要素产出弹性与中国潜在经济增长率

构建了一个结构型时变弹性生产函数,将劳动投入结构、资本投入结构和人力资本结构纳入经济增长分析框架,运用1997-2012的省级面板数据估计了这一时期要素产出弹性的动态特征,并估算出中国潜在经济增长率的变化。研究结果表明：近年来潜在增长率下降,主要由资本存量增速下降所导致,但人力资本结构升级减缓了这一趋势。近10年来实际增长率变化主要是受潜在增长率变化影响,2010年以来的经济增速减缓,是由于潜在增长率下降导致,未来政策重心应当从需求管理过度到供给管理,着力开发经济增长的潜力,保证经济增长的可持续性。     

The Hicksian trade cycle with floor and ceiling dependent on capital stock

This article reconsiders the Hicksian multiplier – accelerator model with ‘floor’ and ‘ceiling’. The new thrust is that these constraints are tied to the actual stock of capital, the floor to the depreciation on this stock, the ceiling to capital as a limiting production factor according to the fixed proportions technology that also underlies the principle of acceleration. For capital formation just the Hicksian investment theory is used. The result is one unified model creating economic growth and growth rate cycles.     

Capital maintenance and depreciation over the business cycle

This paper develops and estimates a stochastic general equilibrium model with capital maintenance, which affects endogenously the depreciation rate of capital. The estimate of maintenance series is found to track survey-based measures for Canada quite closely and to generate the procyclical pattern of maintenance observed in the data. We use our model estimates to infer the time profile of equipment capital depreciation in Canadian and US manufacturing. The depreciation rate is estimated to be volatile and highly procyclical in both countries.     

The stock–bond comovements and cross-market trading

We propose an asset pricing model with heterogeneous agents allocating capital to the stock and bond markets to optimize their portfolios, utilizing the dynamic interaction between the two markets. While some agents focus on the stock market and have more expertise in it, the others specialize in the bond market. Based on their comparative advantages in a particular market, heterogeneous agents constantly revise their investment portfolios by taking into account the time-varying stock–bond return comovements and the changing market conditions. Agents׳ collective investment behavior shapes the stock–bond interlinkage, which feedbacks on their subsequent capital allocations. Using monthly US stock and bond data from January 1990 to June 2014, we estimate the vector autoregression model with threshold and Markov switching mechanisms. We find evidence in support of flight-to-quality and show that it is mainly driven by the technical traders who actively sell stocks and buy bonds during periods of high market uncertainty.     

Endogenous capital utilization in a short-run production model: Theory and an empiral application

In order to be consistent with production theory, empirical factor demand analyses must transform capital stock data into information about the flows of capital services derived from the stock. This requires information about the utilization rate which is, however, not generally available. This paper develops and estimates a model of a capital using firm that one can implement using observable data. Capital utilization and depreciation are endogenous and are determined by profit maximization. The consistency of the model with the data is tested by checking whether the estimated parameters satisfy the regularity conditions imposed by the theory. The validity of the customary specification of an exogenous, price-independent rate of depreciation is also tested.     

Evolving Market Efficiency with an Application to Some Bulgarian Shares

With new technically advanced methods and computers at our disposal, the efficient market hypothesis is once again being debated. At the same time, we are witnessing an unprecedented growth in both existing and new financial markets. These new markets are often in economies which have just recently embraced free market economics; we term these stock markets infant markets. Such stock markets are obviously not efficient in allocating the supply of savings to productive capital. We do not test whether or not these infant markets are informationally efficient, but instead examine whether and how they are becoming more efficient. We propose modelling the excess returns of individual securities using a multi-factor model with time-varying coefficients and generalised auto-regressive conditional heteroskedastic (GARCH) errors. If the markets are becoming more informationally efficient or the agents are learning, we would expect this to manifest itself as the time-varying coefficients becoming more stable as time increases. We test our model using data on four Bulgarian shares. First, we estimate an AR(2) model and a GARCH-M(1,1) model for the shares. Then, we estimated our AR(2) model with time varying coefficients and GARCH type errors. We find varying levels of efficiency and varying speeds of movement towards efficiency within our sample of four shares. This revised version was published online in July 2006 with corrections to the Cover Date.     

Time-varying higher-order conditional moments and forecasting intraday VaR and Expected Shortfall

We estimate several GARCH- and Extreme Value Theory (EVT)-based models to forecast intraday Value-at-Risk (VaR) and Expected Shortfall (ES) for S&P 500 stock index futures returns for both long and short positions. Among the GARCH-based models we consider is the so-called Autoregressive Conditional Density (ARCD) model, which allows time-variation in higher-order conditional moments. ARCD model with time-varying conditional skewness parameter has the best in-sample fit among the GARCH-based models. The EVT-based model and the GARCH-based models which take conditional skewness and kurtosis (time-varying or otherwise) into account provide accurate VaR forecasts. ARCD model with time-varying conditional skewness parameter seems to provide the most accurate ES forecasts.     

Booms,busts and behavioural heterogeneity in stock prices

We estimate a behavioural heterogeneous agents model with boundedly rational traders who know the fundamental stock price, but disagree about the persistence of deviations from the fundamental. Some agents (fundamentalists) believe in mean-reversion of stock prices, while others (chartists) expect a continuation of the trend. Agents gradually switch between the two rules, based upon their relative performance, leading to self-reinforcing regimes of mean-reversion and trend-following. For the fundamental benchmark price we use two well-known models, the Gordon model with a constant risk premium and the Campbell-Cochrane consumption-habit model with a time-varying risk premium. We estimate a two-type switching model using U.S. stock prices until 2016Q4. The estimations show an improvement over representative agent models that is both statistically and economically significant. Our model suggests that behavioural regime switching strongly amplifies booms and busts, in particular, the dot-com bubble and the financial crisis in 2008.     

Testing for predictability in equity returns for European transition markets

This paper presents empirical evidence of short and long-run predictability in stock returns for European transition economies. We employ variance ratios with a bootstrap methodology to test for short-run predictability, which is present in most countries. We also estimate Hurst exponents to test for long-range dependence, and find evidence of such. Furthermore, we find evidence of strong time-varying long-range dependence in these economies stock returns, which is in line with evidence of multifractality of equity returns.     

The half-life of knowledge and strategic human capital

The strategic human capital literature has largely overlooked the fact that knowledge stocks depreciate and that the speed of depreciation varies across settings and over time. We argue that the value of knowledge has a half-life and that numerous core predictions from the conventional human capital analysis change as the half-life shortens. This applies to the ability to extract rents from human capital, employee mobility patterns, employees' disincentive to invest in firm-specific human capital, and more. We also show that, at the limit, a sufficiently rapid rate of knowledge depreciation eliminates the importance of the distinction between general and firm-specific human capital for appropriation and employee mobility.