Institutional dynamics and access to non-farm employment in rural China, 1950–1996

This article examines non-farm employment in the context of Chinese rural institutional change, based on evidence from discrete-time logistic models for event history analysis using the Life History and Social Change survey. We find the transition to non-farm sector rose rapidly during the Great Leap Forward and market reform, while the Cultural Revolution saw it reach the lowest ebb. While male advantage prevailed exclusively during the Cultural Revolution and early marketization, education possessed a stable positive effect in all historical periods. Although the returns to different kinds of political capital vary along with institutional dynamics, intergenerational reproduction was greatly reduced after the Cultural Revolution.     

银行业联合授信制度制约企业的非效率投资了吗*——基于沪深A股公司的分析

中国银保监会出台联合授信管理制度旨在抑制企业过度融资行为，提高资金使用效率。为检验该制度是否达到预期效果，采用2014—2018年沪深A股上市公司样本，运用非平衡面板数据回归实证考察联合授信机制对企业非效率投资的影响，发现联合授信对企业的非效率投资（包含投资不足和投资过度）呈现显著抑制效应，其中联合授信对投资过度的抑制效应最大。进一步研究发现，相较于国有、大规模、低负债、高盈利等异质属性的企业，联合授信对非国有、小规模、高负债、低盈利等属性企业的非效率投资（尤其是投资过度）抑制效应更为显著。     

Best classification algorithms in peer-to-peer lending

A proper credit scoring technique is vital to the long-term success of all kinds of financial institutions, including peer-to-peer (P2P) lending platforms. The main contribution of our paper is the robust ranking of 10 different classification techniques based on a real-world P2P lending data set. Our data set comes from the Lending Club covering the 2009–2013 period, which contains 212,252 records and 23 different variables. Unlike other researchers, we use a data sample which contains the final loan resolution for all loans. We built our research using a 5-fold cross-validation method and 6 different classification performance measurements. Our results show that logistic regression, artificial neural networks, and linear discriminant analysis are the three best algorithms based on the Lending Club data. Conversely, we identify k-nearest neighbors and classification and regression tree as the two worst classification methods.     

基于循环经济的绍兴休闲观光农业发展研究

［目的］休闲观光农业建设是绍兴市产业转型升级的关键一步，探寻休闲观光农业新模式，能够为休闲农业发展提供理论参考。［方法］文章采用变异系数法确定指标权重，多因素综合分析法测算观光农业发展水平，从循环经济角度出发，评价2001—2016年绍兴市休闲观光农业发展可持续性，提出发展中存在的问题并探索循环型的休闲观光农业新模式。［结果］（1）2001—2016年以来，经济发展可持续性得分较高，资源环境可持续得分次之，循环经济可持续发展偏低。（2）现阶段绍兴市休闲观光农业发展主要存在休闲观光农业自然环境不断遭到破坏，休闲观光农业缺乏整体规划，休闲观光农业旅游支撑体系不够健全等问题。（3）未来发展中，循环经济发展下的休闲观光农业可以开发建设时空复合循环型、资源综合利用循环型、能量多级利用循环型、综合开发利用循环型等4种模式。［结论］未来绍兴市应将循环经济的理念融入到休闲观光农业中，因地制宜，科学选择循环型休闲观光农业发展模式； 规划先行，科学利用农业旅游资源； 强化保障，建立休闲观光农业支撑体系，全面推动休闲观光农业健康持续发展。     

Mobile diaries – Benchmark against metered measurements: An empirical investigation

Researchers seeking to study the relationships between consumers' communications, attitudes, and behaviors could benefit from monitoring consumers over time, across multiple locations and channels, and in a way that reflects consumers' subjective perceptions. Diaries on smartphones (mobile diaries) can be used as a research tool for such purposes. A mobile diary is a self-report instrument whereby people use their mobile handset to repeatedly report experiences of interest. Mobile diaries are increasingly used in psychology, geography, medicine, and commercial marketing. Yet they have rarely been used for quantitative marketing research, and were not benchmarked against best-practice metrics in marketing.In this study, we aim to set the ground for using mobile diaries in quantitative marketing research. We first lay out the theoretical infrastructure for the usage of mobile diaries, and describe possible respondent reporting concerns, including concerns related to non-reporting, reporting over time, and concerns stemming from individual-level heterogeneity.We demonstrate the potential of mobile diaries, as well as the importance of the various concerns, using a benchmark test case in the context of primetime TV viewing. Our benchmark uses a sample of respondents with both mobile diary viewing reports and Nielsen People Meter (NPM) records. Our analysis reveals that averaging across all conditions, 47.4%–64.7% of the NPM records are reported by the diary. The major sources for mismatch are random time periods without alarms, short viewings, and periodic reporting inactivity (pulsing). Concerns such as a decrease in reporting rates over time (e.g., fatigue), smartphone ownership, and demographic variation across individuals have relatively small effects on reporting likelihood. Analyzing the cases in which diary reports do not have a matching NPM record, we find many of them can be attributed to out-of-home viewing and viewing on non-metered devices. This finding demonstrates how mobile diaries can complement metered measurements. Overall, aggregate diary-based ratings have a 0.90 correlation with NPM ratings.We discuss implications for designing and using mobile diary studies in marketing.     

Predicting credit card delinquencies: An application of deep neural networks

The objective of this paper is twofold. First, it develops a prediction system to help the credit card issuer model the credit card delinquency risk. Second, it seeks to explore the potential of deep learning (also called a deep neural network), an emerging artificial intelligence technology, in the credit risk domain. With real-life credit card data linked to 711,397 credit card holders from a large bank in Brazil, this study develops a deep neural network to evaluate the risk of credit card delinquency based on the client's personal characteristics and the spending behaviours. Compared with machine-learning algorithms of logistic regression, naive Bayes, traditional artificial neural networks, and decision trees, deep neural networks have a better overall predictive performance with the highest F scores and area under the receiver operating characteristic curve. The successful application of deep learning implies that artificial intelligence has great potential to support and automate credit risk assessment for financial institutions and credit bureaus.     

河北省北部山区农村生态环境治理及绩效评价

[目的]农村生态环境是一个复杂的系统,严重的生态环境问题制约着农村经济的发展以及新农村建设,探讨其治理和绩效,有利于解决生态环境建设中的各种问题,对于区域发展具有重要的理论和实践意义。[方法]文章通过构建农村生态环境治理及绩效评价指标体系,采用层次分析法确定各个指标的权重以及灰色关联法分析各指标间的灰色关联度。[结果]河北省北部山区农村生态环境治理绩效评价指标体系要素层中权重值大小依次为生态经济(0. 483 9)、生态环境(0. 273 6)、生态人居(0. 137 1)、生态保护(0. 105 4),说明该地区农村经济水平已达到一定水平,但生态环境、生态保护等仍有待提高。灰色关联法计算结果表明河北省北部山区生态环境中关联系数最高的是畜禽粪便处理率(0. 754),生态经济中关联系数最高的是农民人均纯收入(0. 624),生态保护中关联系数最高的是化肥施用量(0. 846),生态人居中关联系数最高的是饮用水合格率(0. 682),而关联度大小依次为生态保护(0. 724)、生态环境(0. 662)、生态人居(0. 573)、生态经济(0. 543),说明该地区生态环境治理仍有很大空间。[结论]研究结果指出河北省北部山区农村生态环境治理的不足,为进一步完善区域生态环境具有重要的指导意义。     

新时代耕地占补平衡的逻辑根源、模式探索与管理创新——基于“新时代耕地占补平衡方式改进与管理创新研讨会”的思考

研究目的:对耕地占补平衡的发展阶段与政策绩效、存在问题与逻辑根源进行分析,对改进方式进行探讨,进而提出管理创新建议,为新时代耕地占补平衡政策实施提供科学依据,为促进城乡融合、扶贫攻坚和乡村振兴提供参考。研究方法:综合分析与系统推理。研究结果:(1)耕地占补平衡存在实质性不平衡、时空性不平衡、政策性弱化等微观、中观及宏观层面问题;(2)在数量方面,通过盘活宅基地增量、存量和完善易地调剂方式,统筹城乡和区域平衡来实现数量占补平衡。(3)在质量方面,通过优化建设用地约束指标、完善耕地质量评价、规范耕作层保护与再利用等促进耕地质量占补平衡。(4)在生态方面,通过完善指标调剂的价格内涵、扩大耕地补偿标准范围、转变耕地补充途径等实现耕地生态占补平衡。研究结论:建议做好顶层设计,抓好规划引领,构建耕地占补平衡与城乡要素流动的平衡机制,建立耕地占补平衡后续生态管护长效机制,提升软硬实力等。     

纳税信用评级结果披露与研发投入

以纳税信用评级披露作为一个天然外生冲击,并基于2013—2016年1214家A股上市公司的微观数据构造准自然实验,使用双重差分法系统评估纳税信用评级结果披露对上市公司研发投入的影响。结果发现:纳税信用评级结果披露显著增加了上市公司的研发投入。基于PSM-DID方法的估计结果与上述结论无明显差异。稳健性检验也表明上述结论的正确性。机制检验表明,纳税信用评级结果披露通过降低企业的融资约束,进而促进企业增加研发投入。此外,分样本回归发现纳税信用评级结果披露只能对中小型企业和民营企业的研发投入产生促进作用。     

Do capital flows drive credit growth and consumption in Central and Eastern Europe?

Domestic credit expansion in CEE economies, fuelled in part by foreign capital inflows, helped increase household welfare before the 2008 financial crisis caused a contraction across the region. How strong are the linkages between the current account, domestic credit and consumer spending? This study compiles a quarterly dataset of domestic credit as a share of GDP for 11 CEE European Union members and isolates structural breaks in the series’ growth rates that often align with the 2008 crisis. Vector autoregressive methods, particularly impulse response functions, show that increased current-account deficits lead to increased consumption in six of the 11 countries and increased credit growth in three, and that shocks to credit growth increase consumption in six countries. Capital inflows significantly increase consumption through domestic credit in Slovenia, while the Baltics show a large share of significant effects.