创新驱动下中国区域高质量发展——基于平衡充分发展水平的门槛分析

创新驱动是破解中国区域不平衡不充分发展的突破口,是实现高质量发展的助推器。采用2003～2017年中国30个省市面板数据,运用全局参比Malmquist模型测度了中国区域高质量发展水平,并通过构建指标体系分别对中国各省市的平衡发展和充分发展水平进行了评价,然后通过门槛回归模型分析了在不同平衡和充分发展水平下创新驱动对于高质量发展的影响机制。结果发现：①区域高质量发展水平呈现出先下降后上升的变化趋势；②各省市平衡和充分发展水平均呈现上升趋势,但各省市之间的变化情况差异较大,有明显的空间集聚特征；③在不同的平衡及充分发展水平下,创新驱动对高质量发展的影响机制是不同的,当平衡充分发展水平较低时,创新驱动对高质量发展没有显著影响；当平衡充分发展达到一定水平时,创新驱动对高质量发展起到一定的促进作用；随着平衡充分发展水平的进一步提高,创新驱动对高质量发展的促进作用越来越大。     

Threshold effect of economic openness on bank risk-taking: Evidence from emerging markets

This paper investigates the non-linear effects of two aspects of economic openness, namely, trade openness and financial openness, on banking system stability. We use a panel of 42 emerging markets from 2000 to 2014 to test whether bank risk-taking behaviour varies with the level of openness. We find that a higher degree of trade openness promotes bank stability linearly. Conversely, the non-linear effect of financial openness on bank risk-taking is evident. When the financial system is not sufficiently open, the impact of financial openness on bank stability is insignificant. However, as the domestic financial market becomes more open, financial openness can help discipline the behaviour of banks, making them more stable. We also find evidence that these effects are transmitted through the market discipline channel. Our findings highlight the importance of strengthening the domestic regulatory framework and transparency as the economy becomes more integrated.     

Separate waste collection in mountain municipalities. A case study in Campania

This paper aims to analyse the impact of land characteristics (i.e. altimetry and housing dispersion) on separate waste collection, with a focus on mountain municipalities. The high spatial heterogeneity of the driving factors of separate waste collection allows traditional techniques, such as OLS, to offer only a partial depiction of the situation, missing important information. In this view, we perform the Geographically Weighted Regression (GWR), which allows to control for the local determinants of waste management. Our data cover 550 municipalities of Campania, in Southern Italy. We control for a set of morphological and socio-economic variables, drawn from official records for 2012. Our results show that the relationships between land characteristics and separate waste collection are not constant over space. Moreover, they suggest that in the presence of non-modifiable factors (such as land characteristics) local governments should act on citizen motivations, promoting awareness on environmental issues, and should implement time-saving collection methods.     

The use of landslide hazard maps to determine mitigation priorities in a dam reservoir and its protection area

Despite longstanding research on the landslide hazard assessment and mapping, the use this information in regional planning applications remains largely unclear. There is still a need for novel methods to interpret the results of hazard analyses. In this respect, the main research question of this study is how the landslide hazard maps can be evaluated in planning practice. To evaluate this issue, a comprehensive case study was carried out and a new methodology, defining the order of priority for the locations where mitigation measures are applied was developed. The investigations were carried out in the Melen Dam reservoir, which provides potable water to the city of Istanbul, and the dam protection area (Duzce, Turkey) in four main stages: (i) Evaluation of the general characteristics of the study area, (ii) preparation of landslide inventory, (iii) development of landslide hazard model, and (iv) implementation of the results of hazard analyses in planning. As a consequence, a decision support system that can evaluate analytically complicated outputs “P_Combined”, “P_{AL min.}”, and “L_Total” and provide clear decisions “Urgent”, “Primary”, and “Secondary” was suggested. Considering the limited resources available for the mitigation measures, the determination of mitigation priorities for the micro-catchments constitutes the key land-use policy for the protection of the dam reservoir.     

LADM-based profile for farmland Tripartite Entitlement System in China

Since the beginning of the 21st century, China has undergone a promotion of industrialisation, urbanisation and agricultural modernisation. This promotion has triggered the mass migration of rural labour forces into cities, leading to the virtual situation of the separation of farmland contract and operation rights. To respond to this issue, the central government proposed a strategy of farmland reform in China. Such reform aims to transform the former ‘Bipartite Entitlement System’ into a ‘Tripartite Entitlement System (TES)’.¹ Land registration provides the means for recognising formalised property rights and regulating the characteristics and transfer of land-related rights. As for farmland registration in China, it serves as a basis to explore effective forms of collective farmland ownership by implementing collective farmland ownership, stabilising farmers’ contract rights and liberalising farmland operation rights. Thus, in this study, on the basis of the farmland tripartite entitlement (hereinafter referred to as ‘FTE’) reform in China, we develop a Land Administration Domain Model (LADM)-based TES model that will serve as the basis of subsequent system development. Specifically, first, we summarise the evolution process of China’s farmland rights system since the foundation of new China. Second, we propose a farmland rights system after the FTE reform. Then, the corresponding TES model is developed based on the LADM standard and some instance-level diagrams for farmland administration activities. The new functionality of the model includes improved structuring of farmland rights and restrictions (and related source documents) and improved expansion of the land information infrastructure to rural areas.     

Relationships between absenteeism,conservation group membership,and land management among family forest owners

Absentee landowners, or those who do not live on their forestland, own approximately 117 million acres of private forestland in the U.S. Thus, their land management decisions and activities influence the flow of forest-based goods and services. We explore the question of whether absentee family forest owners are less active land managers than resident landowners and whether membership in conservation organizations is associated with higher levels of land management activity by absentee owners. To examine these questions, we administered a mail survey to randomly-selected family forest landowners in Indiana. While we found some support for the contention that absentee owners are less active forestland managers than resident owners, we also found they are not necessarily inactive landowners. We found absentee owners were less likely to have: inspected their forestland for invasive plants, pulled or cut invasive plants, used herbicides to kill invasive plants, reduced fire hazard, or grazed livestock than resident owners. Absentee owners were more likely to be enrolled in the Indiana Classified Forest and Wildlands Program, a preferential forest property tax program. Absentee owners who are members of a conservation organization were more likely than absentee non-member owners to have undertaken a variety of land management activities, including: undertaking wildlife habitat improvement projects, inspecting their forestland for invasive plants, pulling or cutting invasive plants, enrolling in the Indiana Classified Forest and Wildlands program, and obtaining a management plan.     

Brexit: Tracking and disentangling the sentiment towards leaving the EU

On 23 June, 2016, the UK held a referendum to decide whether to stay in the European Union or leave. The uncertainty surrounding the outcome of this referendum had major consequences for public policy, investment decisions, and currency markets. We discuss some of the subtleties involved in smoothing and disentangling poll data in light of the problem of tracking the dynamics of the intention to Brexit, and propose a multivariate singular spectrum analysis method that produces trendlines on the unit simplex. The trendline yield via multivariate singular spectrum analysis is shown to resemble that of local polynomial smoothing, and singular spectrum analysis presents the nice feature of disentangling the dynamics directly into components that can be interpreted as changes in public opinion or sampling error. The merits and disadvantages of some different approaches for obtaining smooth trendlines on the unit simplex are contrasted, in terms of both local polynomial smoothing and multivariate singular spectrum analysis.     

High-frequency credit spread information and macroeconomic forecast revision

We examine whether professional forecasters incorporate high-frequency information about credit conditions when revising their economic forecasts. Using a mixed data sampling regression approach, we find that daily credit spreads have significant predictive ability for monthly forecast revisions of output growth, at both the aggregate and individual forecast levels. The relationships are shown to be notably strong during ‘bad’ economic conditions, which suggests that forecasters anticipate more pronounced effects of credit tightening during economic downturns, indicating an amplification effect of financial developments on macroeconomic aggregates. The forecasts do not incorporate all financial information received in equal measures, implying the presence of information rigidities in the incorporation of credit spread information.     

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.     

Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High-Dimension Regime

In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high-dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real-data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression.