Asymmetric effects of housing wealth on college enrolment

We investigate the impact of housing wealth, credit availability and financial distress on college enrolment decisions. We find that housing wealth is negatively related to enrolment in public schools and positively related to enrolment in private schools. This evidence suggests that, on average, students substituted away from private schools towards public institutions during the recent financial crisis.     

Recognition versus disclosure of finance leases: Evidence from Japan

This study examines whether credit market participants—bond investors and credit rating agencies—treat recognized and disclosed finance leases differently when assessing firms’ credit risk in Japan. I use firms’ credit risk, measured by bond spreads and credit ratings, to investigate the relations between recognized versus disclosed finance lease obligations and firms’ credit risk following the adoption of Statement No. 13, Accounting Standard for Lease Transactions. For a sample of firms issuing new bonds, I find that, unlike recognized finance leases, disclosed finance leases are not associated with bond spreads. Moreover, the associations between recognized versus disclosed finance leases and bond spreads are substantially different. Conversely, recognized and disclosed finance leases are associated with credit ratings and are processed similarly when credit ratings are determined. Taken together, my results suggest that the sophistication of capital market participants influences their credit risk assessments of recognized versus disclosed finance leases.     

Dynamic response of bank-intermediated trade finance to a global liquidity shock

This paper investigates the bank-level responses of a bank-intermediated instrument of trade finance to a negative global liquidity shock in Korea. Using a factor-augmented vector autoregression approach, the results show that there exists significant heterogeneity in bank-level trade-finance responses to a global liquidity shock. In addition, we find that the source of the heterogeneity is the bank-level foreign currency liquidity condition; banks with a better foreign currency liquidity condition may dampen the negative impact of a global liquidity shock on trade-finance.     

新疆坎儿井农业遗产资源保护与旅游开发利用

[目的]分析新疆坎儿井农业文化遗产资源的旅游效用,以期更好地指导当地旅游资源的开发利用工作,达到促进区域休闲农业可持续发展的目的。[方法]文章以新疆坎儿井农业文化遗产资源为例,分析其资源特征、资源保护及开发现状;采用AHP分析法分析坎儿井农业遗产资源旅游效用,基于上述分析并结合农业文化遗产旅游发展的需求,提出优化其农业遗产资源保护及开发的规划、模式及策略。[结果]坎儿井农业文化遗产资源中主体旅游资源坎儿井工程(B_1)、辅助旅游资源农业文化资源(B_2)、客源与市场特征(B_3)和外部因素特征(B_4)的权重分别是0.43、0.22、0.10和0.06。[结论]在比较其生态价值、环保价值、旅游价值的基础上,发现在稳固生态价值与环保价值的同时,挖掘新疆坎儿井的旅游价值是实现农业文化遗产有效保护的最佳途径;主体旅游资源坎儿井工程和辅助旅游资源农业文化资源为坎儿井农业遗产资源旅游带来良好的经济收益,而客源与市场特征和外部因素特征权重最低,说明这两个因素是导致旅游效益权重低的主要原因;农业遗产资源旅游的保护和开发两者互惠共赢,但必须建立在重视农业遗产资源的保护及其宣传保护的基础上。     

中国区域农业科技资源配置能力及比较优势研究*——基于省级农业科学院视角

[目的]通过测算各地区农业科技资源的配置能力,分析其比较优势并找出不足以便弥补差距,促进各区域农业科技配置能力的提高,为各地区农业经济的发展提供支持。省级农业科学院作为各省市规模最大、综合实力最强的农业科研机构,是农业科技创新的重要主体之一,分析其科技资源配置能力具有重要的现实意义。[方法]基于2009—2016年相关数据,遴选了有代表性的评价指标体系,运用突变级数法计算农业科技资源配置能力,运用NRCA模型定量分析农业科技资源配置效益的比较优势。[结果]山东农业科学院科技资源配置能力位居全国第一,甘肃、江苏、青海农业科学院分别在农业科技人力、物力、财力资源方面具有明显的比较优势。[结论]省级农业科学院科技资源配置能力区域差异十分明显,但区域格局变化不大,且大致与各地区经济实力相吻合;农业科技资源配置能力较高的农业科学院大多在农业科技物力资源配置效益方面具有比较优势,在农业科技人力、财力资源配置效益方面不具备比较优势。     

新中国成立70年农村基本经营制度的历史演进与发展取向——基于农村土地制度和农业经营制度的改革联动视角

研究目的:剖析农村土地制度和农业经营制度的关系,为完善农村基本经营制度提供参考。研究方法:比较分析法、文献研究法。研究结果:新中国成立70年来,农村基本经营制度先后历经新中国成立初期的"农民所有、家庭经营"、改革开放前期的"集体所有、集体经营"到改革开放后期的"集体所有、均田承包、家庭经营",再到现阶段的"集体所有、均田承包和多元经营"4个阶段。在这个过程当中,农村基本经营制度既遵循人口与土地关系、生存与发展关系以及政府与市场关系的大逻辑,又遵循着农村土地制度的"产权逻辑"、农业经营制度的"生产逻辑"等小逻辑。研究结论:为深化农村基本经营制度变革,需加强农村土地制度与农业经营制度联动改革的制度设计,发挥要素、组织和制度的作用,发展多种形式的适度规模经营,实现小农户与现代农业发展的有机衔接。     

Market impact: a systematic study of the high frequency options market

This paper deals with a fundamental subject that has seldom been addressed in recent years, that of market impact in the options market. Our analysis is based on a proprietary database of metaorders—large orders that are split into smaller pieces before being sent to the market—on one of the main Asian markets. In line with our previous work on the equity market [Said, E., Bel Hadj Ayed, A., Husson, A. and Abergel, F., Market impact: A systematic study of limit orders. Mark. Microstruct. Liq., 2018, 3(3&4), 1850008.], we propose an algorithmic approach to identify metaorders, based on some implied volatility parameters, the at the money forward volatility and at the money forward skew. In both cases, we obtain results similar to the now well-understood equity market: Square-Root Law, Fair Pricing Condition and Market Impact Dynamics.     

The Impact of Public Expenditure and International Trade on Agricultural Productivity in China

The “industry nurturing agriculture” reforms and World Trade Organization accession led to dramatic growth in public expenditure and international trade in China’s agricultural sector. This article aims to estimate the effects of public expenditure and trade on agricultural productivity in China for 2004–2015. A semi-parametric production function with shape constraints is introduced to derive more accurate productivity before the productivity determinants are analyzed with an emphasis on public expenditure and trade. The empirical result shows that public expenditure and exports can effectively improve agricultural productivity, while imports have no significant effects. Policy implications are discussed in the context of supply-side reforms.     

河南省农业生态旅游产业可持续发展评价研究

[目的]河南农业生态旅游作为一种可持续发展的旅游形式,为河南的经济发展作为了重要贡献。对河南农业生态旅游产业可持续发展进行评价研究,是促进农业生态旅游可持续健康发展的重要保证。[方法]文章通过实地调研构建河南农业生态旅游产业可持续发展评价指标体系,运用层次分析法,确定指标权重,结合专家评分法,对各项评价指标打分,并计算河南农业生态旅游产业可持续发展的综合得分,结合农业生态旅游产业可持续发展评价标准,得出目前河南农业生态旅游产业可持续发展水平。[结果]河南农业生态旅游产业可持续发展评价得分为72.45,处于基本可持续发展阶段,并对当前河南农业生态旅游发展现状和存在的农业生态旅游意识淡薄、旅游产品特色不明显、缺少政府资金扶持和缺乏经营管理人才等问题进行了分析。[结论]基于上述问题,提出了提高环保意识、走可持续发展之路;开发特色原生态旅游产品;加强政府支持和引导;加强专业培训,打造专业队伍等对策。     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.