The cointegrated vector autoregressive model with general deterministic terms

In the cointegrated vector autoregression (CVAR) literature, deterministic terms have until now been analyzed on a case-by-case, or as-needed basis. We give a comprehensive unified treatment of deterministic terms in the additive model $X_t=\gamma Z_t+Y_t$, where $Z_t$ belongs to a large class of deterministic regressors and $Y_t$ is a zero-mean CVAR. We suggest an extended model that can be estimated by reduced rank regression, and give a condition for when the additive and extended models are asymptotically equivalent, as well as an algorithm for deriving the additive model parameters from the extended model parameters. We derive asymptotic properties of the maximum likelihood estimators and discuss tests for rank and tests on the deterministic terms. In particular, we give conditions under which the estimators are asymptotically (mixed) Gaussian, such that associated tests are ${\chi }^2$-distributed.     

Japan's FDI drivers in a time of financial uncertainty. New evidence based on Bayesian Model Averaging

In this paper we analyse the determinants of Japanese outward FDI stock for the period 1996–2017. This period is especially relevant as it covers a process of increasing economic globalization and two financial crises. To this aim, we consider a large set of candidate variables based on the theory as well as on previous empirical analysis. Our sample includes a total of 27 host countries. We select the covariates using a data-driven methodology, the Bayesian Model Averaging (BMA) analysis. Moreover, we also analyse whether these determinants change depending on the degree of development (emerging vs developed) or the geographical areas (EU vs East Asia) of the countries considered. We find that Japan's FDI can be explained by a wide variety of variables, that include not only the typical gravitational ones but also institutional and macroeconomic variables, including those that measure financial development. Moreover, Japanese FDI can be explained by both horizontal and vertical FDI motives in the groups of countries analysed. However, in developed, and more precisely, EU countries, horizontal FDI strategies are predominant, whereas for East Asian and emerging countries, there is more evidence in favour of vertical FDI.     

广东省县域农业生产效率分析——基于2015-2019年揭阳市5县域DEA模型为例

农业生产效率提升是实现农业现代化的重要手段。本文以《揭阳市统计年鉴(2015-2019)》的农业相关数据,从县域的视角研究揭阳市农业生产效率,运用DEA模型对揭阳市5个县域的3个投入指标和1个产出指标进行实证分析。结果显示,2015-2019年揭阳市农业生产效率均属于DEA无效,总体效率提升并不明显,且各县域呈现发展不平衡的状态,仅惠来县位于生产前沿面上,普宁市的农业生产效率最低,规模报酬属于递减态势。因此,恰逢“十四五”谋划之时,对揭阳市各县域农业生产效率做出分析研究,为现阶段提升揭阳市农业生产效率提出有参考价值的建议,为广东省县域农业生产效率分析提供范本。     

Price connectedness between green bond and financial markets

We study price connectedness between the green bond and financial markets using a structural vector autoregressive (VAR) model that captures direct and indirect transmission of financial shocks across markets. Using heteroskedasticity to identify the structural VAR model parameters, our empirical findings reveal that the green bond market is closely linked to the fixed-income and currency markets, receiving sizeable price spillovers from those markets and transmitting negligible reverse effects. We also show that, in contrast, the green bond market is weakly tied to the stock, energy and high-yield corporate bond markets. These findings have implications in terms of portfolio and risk management decisions for environmentally aware investors holding positions in green bonds.     

An information-theoretic approach for forecasting interval-valued SP500 daily returns

We develop an iterative and efficient information-theoretic estimator for forecasting interval-valued data, and use our estimator to forecast the SP500 returns up to five days ahead using moving windows. Our forecasts are based on 13 years of data. We show that our estimator is superior to its competitors under all of the common criteria that are used to evaluate forecasts of interval data. Our approach differs from other methods that are used to forecast interval data in two major ways. First, rather than applying the more traditional methods that use only certain moments of the intervals in the estimation process, our estimator uses the complete sample information. Second, our method simultaneously selects the model (or models) and infers the model’s parameters. It is an iterative approach that imposes minimal structure and statistical assumptions.     

Forecasting value at risk and expected shortfall with mixed data sampling

I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence on short-horizon returns to directly forecast the tail dynamics of the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially in terms of multi-day forecast horizons. My analysis advocates models that feature asymmetric conditional quantiles and the use of the Asymmetric Laplace density to jointly estimate VaR and ES.     

房价上涨如何影响了工业产出

为探究房价上涨对工业生产的作用机制,首先基于理论视角对房价如何影响房地产投资、劳动力成本进而影响工业产出进行了论证,基于2003年~2017年全国时间序列数据,构建VAR模型实证检验了房价上涨对工业产出的影响机理。结果表明:房价上涨对工业产出具有"先促进,后抑制"的作用;房价上涨,一方面通过促进房地产投资增长抑制工业产出,另一方面通过提高工业企业劳动力成本抑制工业产出;短期内工业产出对房价的冲击响应较为灵敏且强烈,但长期来看房地产投资、劳动力成本的影响力会逐渐显现,且房地产投资最终成为了解释工业产出的主导因素。     

外商直接投资、区域创新与城市化发展研究

基于2000—2017年省际面板数据,运用静态面板与门限面板模型,通过建立以政府干预、市场化进程为门限变量的回归模型,实证分析了外商直接投资与区域创新对我国城市化发展的影响。研究结果表明:外商直接投资、区域创新对城市化发展有积极的带动作用,同时,外商直接投资对区域创新的作用由替代效应向互补效应转变;政府干预对外商直接投资存在双重门限效应,对区域创新存在单一门限效应;市场化对外商直接投资存在单一门限效应,但对区域创新存在双重门限效应。基于以上结论,进一步提出促进城市化发展的建议。     

网络强度、组织冗余与创新模式——对200家样本企业问卷调研数据的实证检验

通过社会网络带来资源冗余进而对创新选择产生影响，这一机制已成为当今企业可持续发展的重要路径。运用200份企业样本调研数据，对网络强度、不同类型组织冗余及两种创新模式进行实证检验，结果发现，网络强度显著正向直接影响利用式创新和探索式创新;网络强度还通过正向影响未吸收冗余对两种创新产生正向间接影响作用;未吸收冗余与创新模式间具有显著正向影响关系,而吸收冗余在三者影响路径关系中检验结果不显著，可能是受企业自身因素或条件影响所致。最后，根据研究结论提出3点重要管理启示。     

产军协同、政府科技支持与技术创新效率研究

运用空间数据分析方法，检验产军协同、政府科技支持与技术创新效率在我国省域间的分布格局。研究表明，三者均存在显著的正向空间相关性，即正向空间溢出效应，并且在不同地区形成局部空间集聚，存在高低非均衡的“俱乐部”现象。基于空间误差模型和空间滞后模型，实证检验产军协同、政府科技支持对技术创新效率的影响。结果发现，从全国和分地区看，产军协同、政府科技支持均能够显著促进技术创新效率提升，并且二者存在显著的交互作用，能够发挥彼此间的互补效应，进一步促进技术创新效率提升；不同地区产军协同、政府科技支持对技术创新效率的影响程度存在较大差异，西部地区产军协同、政府科技支持对技术创新效率的促进作用比东部和中部地区显著。