Application of Bayesian Econometrics in Policy Evaluation

This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including the concepts of Bayesian inference, prior distributions, and posterior distributions. Through systematic analysis, the study constructs a theoretical framework for applying Bayesian methods in policy evaluation. The research finds that Bayesian methods have multiple theoretical advantages in policy evaluation: Based on parameter uncertainty theory, Bayesian methods can better handle uncertainty in model parameters and provide more comprehensive estimates of policy effects;from the perspective of model selection theory, Bayesian model averaging can reduce model selection bias and enhance the robustness of evaluation results;according to causal inference theory, Bayesian causal inference methods provide new approaches for evaluating policy causal effects. The study also points out the complexities of applying Bayesian methods in policy evaluation, such as the selection of prior information and computational complexity. To address these complexities, the study proposes hybrid methods combining frequentist approaches and suggestions for developing computationally efficient algorithms. The research also discusses theoretical comparisons between Bayesian methods and other policy evaluation techniques, providing directions for future research.

The Impact of Urbanization and Factor Inputs on China's Economic Growth--A Spatial Econometrics Approach

This paper utilizes a panel data of 31 provinces in China spanning from 2007 to 2014.Spatial econometrics is applied to carry out regression analysis of the impact of urbanization and factor inputs on China's economic growth.By comparing differences among regions,this paper finds that in the regional level,the positive effect of urbanization in the Eastern region and the Western region is significant,and the positive effect of the proportion of input factors in the Central region is also significant but to a lesser extent.In general,there exists spatial spill-over effect between urbanization and factor inputs structure and economic growth,i.e.,both are capable of producing positive effect,but the input role played by the scale factor has diminishing marginal effect.Urbanization is more likely to become the driving force of economic growth and to stimulate economic growth.

Innovative Research on the Blending Learning Mode of Econometrics

Due to the outbreak of the Covid-19 in 2020,online education has become the mainstream.After the epidemic,the blending learning mode has also become a key goal of the teaching reform of colleges and universities,and the blending learning mode of various courses has blossomed everywhere.In this context,this paper used the Econometrics course as the carrier,analyzed the many unreasonable problems in the traditional Econometrics course,and proposed an optimization plan and path for the blending learning mode to address these problems.

Causal inference using regression-based statistical control: Confusion in Econometrics

Regression is a widely used econometric tool in research. In observational studies, based on a number of assumptions, regression-based statistical control methods attempt to analyze the causation between treatment and outcome by adding control variables. However, this approach may not produce reliable estimates of causal effects. In addition to the shortcomings of the method, this lack of confidence is mainly related to ambiguous formulations in econometrics, such as the definition of selection bias, selection of core control variables, and method of testing for robustness. Within the framework of the causal models, we clarify the assumption of causal inference using regression-based statistical controls, as described in econometrics, and discuss how to select core control variables to satisfy this assumption and conduct robustness tests for regression estimates.

Using Spatial Econometrics to Measure Ozone Pollution Externalities

This paper summarizes my previous work in Lin (2010), in which I use spatial econometrics to analyze air pollution externalities. In Lin (2010), state-by-state source-receptor transfer coefficients that can be used as a basis for a location- differentiated permit system are estimated. Results affirm the importance of regional transport in determining local ozone air quality, although owing to non-monotonicities in ozone production the externality is not always negative. Because the origin of emissions matters, results also reject a non-spatially differentiated NOx cap and trade program as an appropriate mechanism for reducing ozone smog.

Time Series Econometrics: A Critique

This is a critical note regarding the currently established econometrics of time series. The criticism involves commonly practiced mechanistic modeling and testing of relationships, taking econometrics away from economics. Among others, modeling economic trends as simple functions of time is extremely naive and testing for cointegration lacks a proper economic foundation.

Examine the Reliability of Econometrics Software: An Empirical Comparison of Time Series Modelling

Researchers must understand that naively relying on the reliability of statistical software packages may result in suboptimal, biased, or erroneous results, which affects applied economic theory and the conclusions and policy recommendations drawn from it. To create confidence in a result, several software packages should be applied to the same estimation problem. This study examines the results of three software packages (EViews, R, and Stata) in the analysis of time-series econometric data. The time-series data analysis which presents the determinants of macroeconomic growth of Sri Lanka from 1978 to 2020 has been used. The study focuses on testing for stationarity, cointegration, and significant relationships among the variables. The Augmented Dickey-Fuller and Phillips Perron tests were employed in this study to test for stationarity, while the Johansen cointegration test was utilized to test for cointegration. The study employs the vector error correction model to assess the short-run and long-term dynamics of the variables in an attempt to determine the relationship between them. Finally, the Granger Causality test is employed in order to examine the linear causation between the concerned variables. The study revealed that the results produced by three software packages for the same dataset and the same lag order vary significantly. This implies that time series econometrics results are sensitive to the software that is used by the researchers while providing different policy implications even for the same dataset. The present study highlights the necessity of further analysis to investigate the impact of software packages in time series analysis of economic scenarios.

Fiscal Expenditure and Income Gap between Urban and Rural Residents: An Empirical Study Based on Malmquist Index and Spatial Econometrics

Based on the analysis methods of non-parametric Malmquist index and spatial econometrics as well as the provincial panel data in 2007-2010, this paper estimates the efficiency of fiscal expenditure from local governments in china in terms of reducing the income gap between urban and rural residents for the first time and evaluates the spatial correlation and heterogeneity of this efficiency. The results have shown that the fiscal expenditure of most provinces is of low efficiency in reducing the income gap between urban and rural residents, and the expenditure efficiency of local governments is not relevant to their levels of economic development. Besides, the efficiency on reducing the urban-rural income gap between different regions of China has a tendency of convergence. But this is mainly reflected inside the regional economic belt. There is significant difference between the efficiency of each economic belt. The central region has the highest efficiency in a rising trend, the western region has the lowest efficiency in a downward trend, while the eastern region is relatively stable.

The Evolution of Urban and Rural Construction Land Based on Spatial Econometrics:A Case Study of Bijie City

Based on the theory of spatial econometrics,we test and process the urban and rural construction land data during the base period of planning and late period of planning in Bijie City.And we conduct comparative analysis of the spatial pattern and evolution characteristics of urban and rural construction land in 41 towns of Bijie City before and after the planning.According to Getis-ord G i coefficient test results,the cold spot area of urban and rural construction land in northeast of Bijie City will gradually disappear,and the key point of hot spot area will be gradually transferred from the central region to the central and eastern regions.The results show that under the guidance of the overall land use planning in Bijie City,the urban and rural construction land will show strong spatial autocorrelation;agglomeration benefits and scale merit will appear clearly,in line with the actual situation of current development of Bijie City.

Discussion on Collaborative Teaching of Econometrics in the Field of Environmental Economics

To capitalize on the synergies between the Econometrics course and the Environmental Economics major,this paper aims to enhance students’ability to conduct empirical analysis and practical application using econometric models.It also seeks to promote collaborative teaching through case studies and model research.The primary focus is on the hot research issues within the field of environmental economics,utilizing the econometric model as a vehicle for instruction.To achieve this,the paper proposes the development of a comprehensive case library specific to environmental economics.This resource will serve to optimize the case teaching approach,incorporating the use of econometric software,and fostering interactive teaching models between educators and students.By implementing these strategies,the paper outlines a path and mode for collaborative teaching that effectively bridges the gap between econometrics and environmental economics.

对外开放对全国统一大市场建设的影响研究:基于我国市场分割的视角

双循环新发展格局下,进一步扩大对外开放将成为我国构建全国统一大市场的关键。在分析对外开放影响全国统一大市场建设的理论机制基础上,选取2005—2020年中国省级面板数据,构建空间计量模型,检验对外开放对我国市场分割产生的空间溢出效应,并通过中介效应模型对理论机制进行检验。研究表明:对外开放能显著降低本地区的市场分割程度,具有正向的空间外溢效应;理论机制检验进一步发现,对外开放通过国企股份制改革、基础设施建设以及提高地区经济发展水平三条路径打破市场分割局面,对全国统一大市场建设产生积极效应。

财政分权、地方政府行为与经济绿色转型

依据2009—2019年省级面板数据,运用空间计量模型和中介效应模型,考量财政分权对经济绿色转型的影响。结果显示:财政分权促进本地经济绿色转型作用显著,但会阻碍相邻地区经济绿色转型进程。地方政府行为在二者之间发挥着中介作用,财政分权主要通过促进地方政府合理竞争、提高地方政府财政科技投入强度促进经济绿色转型,提高财政分权程度会强化地方保护主义行为,但地方保护主义行为对经济绿色转型的影响不显著。

绿水青山就是金山银山:生态环境对旅游经济影响的空间计量检验

“绿水青山就是金山银山”揭示了生态环境和经济发展的关系,探究生态环境质量对旅游经济的影响效应,有利于二者比翼双飞与协调发展。以2004-2019年中国31个省(直辖市、自治区,不含港澳台地区)为研究对象,利用空间自相关和空间面板杜宾模型探究生态环境质量对旅游经济的影响效应。结果表明:(1)生态环境质量和旅游经济发展的空间集聚性显著,空间关联性不断增强。(2)生态环境质量不仅对本地区旅游经济发展具有明显的促进作用,对相邻地区也具有溢出效应与示范作用。(3)生态环境质量作为影响旅游经济发展的重要因素,但不能忽略接待设施、资源禀赋、劳动力投入、物质资本、经济发展水平等多维要素的综合作用。要综合考量这些要素,才能促进“绿水青山”向“金山银山”的转换,实现生态环境与旅游经济的协调、健康、高效发展。

引入因果关系分析的本科计量经济学教学改革研究

现代计量经济学已经进入一个以因果识别为重要理论方法的新时代。该文分析国内外高校计量经济学教学改革现状和现代计量经济学范式的转变,提出引入因果关系分析的计量经济学课程改革的意义,介绍计量经济学引入因果关系分析的改革内容设计。该文对于提升本科计量经济学教学水平,培养本科计量经济学人才具有意义。

人口负增长趋势下乡村人口变动对乡村产业振兴的作用机理及空间效应研究

人口负增长趋势下我国乡村地区面临严峻的人口形势,直接影响到乡村振兴战略的实施。研究以2011—2020年全国30个省(自治区、直辖市)面板数据为基础,运用空间计量模型研究乡村人口变动对乡村产业振兴的影响机理及空间溢出效应。研究发现:(1)人口负增长使乡村地区劳动人口减少,消费市场萎缩,投资意愿下降,对产业振兴起到明显抑制作用;(2)乡村人力资本提升、乡村劳动力资源增加及乡村老龄化水平加深均可促进产业振兴的实现;(3)人口负增长、乡村人口变动对乡村产业发展存在空间溢出效应。应通过人才引进、优化劳动力配置等措施来积极应对人口负增长给乡村地区带来的挑战。

农户种植饲草料投入产出及种植行为影响因素研究——以内蒙古巴彦淖尔市杭锦后旗和磴口县为例

国内消费结构及农业结构调整背景下,中国畜牧业迅速发展,饲草料需求不断增加,但是国内饲草料供应不足、安全问题凸显。在“粮改饲”试点旗县进行实地调研,了解当地农户饲草料种植的投入产出情况,利用Logit、2SLS及LIML模型对农户种植饲草料行为的影响因素进行实证研究。结果显示,调查区域农户种植的饲草料主要以青贮玉米、苜蓿及燕麦草为主,种植苜蓿草的经济效益比其他饲草料高,2021年苜蓿草纯收益可达22 005元/hm^(2),比青贮玉米和燕麦草分别高出4 590元/hm^(2)元和12 180元/hm^(2),但是农户种植饲草料尤其苜蓿草的积极性并不高。探究农户选择种植饲草料行为的影响因素,发现政策激励、土地禀赋及组织制度因素对农户饲草料种植行为有显著的正向影响,提出政府应该尽快建立完善的土地流转市场体系,助力农户扩大种植规模,顺利进行种植业结构调整,加大饲草料种植面积,促进为养而种的良性循环,解决养殖业饲草料短缺问题以及鼓励各类合作社发挥合作制度优势,帮助农户降低种植饲草料的投入成本,拓宽饲草料的销售渠道,增加农民收入的对策建议。

知识产权国内贸易对“双循环”有效联动的影响效应

基于知识产权国内贸易、“双循环”有效联动的时空演化特征分析发现,二者发展变化具有显著的内在逻辑一致性。理论分析认为,知识产权国内贸易可以通过加快高水平自主创新、激发高品质消费需求等,对“双循环”有效联动产生显著的促进作用。进一步利用2001—2020年中国省级面板数据开展的计量检验结果表明,第一,知识产权国内贸易对“双循环”有效联动具有积极促进作用;第二,由于知识产权国内贸易、“双循环”有效联动水平存在显著的空间溢出效应,因此,知识产权国内贸易对“双循环”有效联动的促进作用不仅发生在本地区,而且对相邻地区的“双循环”有效联动也有积极促进效应;第三,知识产权国内贸易对“双循环”有效联动的促进作用,因各地区对外开放程度、人力资本水平、城镇化水平、消费水平和知识产权保护水平的差异而存在一定的“门槛特征”。上述研究不仅有助于深化认识知识产权国内贸易对“双循环”有效联动的现实影响和作用机制,而且对于如何通过加强知识产权国内贸易推动“双循环”互促互进也有重要的政策意义。

数字经济如何赋能区域创新能力的提升?

基于2013—2020年省份的面板数据,分别构建了数字经济和区域创新能力的测度指标体系,运用空间杜宾模型分析数字经济发展对区域创新能力的影响。研究结果表明,数字经济发展显著促进区域创新能力提升,对区域创新实力、创新效率和创新潜力均有显著积极作用。同时,数字经济对区域创新能力具有显著的空间溢出效应,不仅提升本地区的创新能力,而且能够带动邻近地区创新能力的提升。进一步分析发现,金融发展水平和市场化程度是数字经济赋能区域创新能力的两条重要路径。异质性分析结果显示,相较于东部地区,数字经济发展对西部地区创新能力的改善效果显著。研究结论为新时代促进区域创新空间优化与协调发展提供理论支撑和政策建议。

南京市景感生态学绿视率指标量化研究

城市绿地是城市生态系统中的关键组成部分,不仅形成生态缓冲区来提升环境质量,还能保障居民的健康与福祉。随着城市区域的持续扩张,科学合理地规划绿地对推动可持续城市发展越来越重要。基于景感生态学的原理,提供了一种评估城市街区内绿化覆盖尺度的定量方法和景感绿视率指标(Landsense Green View,LGV)。这一指标用于捕捉影响环境和心理健康结果的绿化程度。研究聚焦于南京市的中心城区,使用包括人工智能和街景大数据在内的先进手段来精确量化LGV并评估其空间分布。此外,研究采用地理信息系统(Geographic Information System,GIS)来分析空间模式,并利用计量经济学工具来识别和辨析该地区LGV值的影响因素。回归模型的决定系数为0.869,所采用的模型在预测和理解城市中LGV具有可靠性。GIS分析揭示了几个关键结果:1)街区尺度的自然景观显著提升LGV,相反,人工景观则成为阻碍,显著降抑制LGV。2)城市街区内土地使用的功能和多样性对LGV值有显著影响。3)揭示了LGV在南京的分布表现出内外不均衡的现象,具体呈现从城市中心向农村地区递减的城乡梯度。这种梯度揭示了获取城市绿地的生态效益在不同区位存在显著差距,可能会影响城市规划和政策制定。通过理解城市LGV的空间影响因素和规律,城市规划者和环境管理者可以更好地制定绿化资源配置,并优化城市布局从而增强居民可获得的生态服务和社会福利。本研究加深了从以人为本的角度对现有生态绿地在当前状态和空间模式的理解,突出了在城市绿地规划中整合先进的定量工具和空间分析技术的重要性。提出的研究框架,可支持精细化的城市规划和绿色管理策略,旨在提高城市绿地的质量和功能性,有助于实现绿地配置的可持续性和城市韧性目标。

生猪产业低碳发展的研究进展与展望

为探究生猪产业低碳发展研究动态和发展趋势,本文基于web of science(WOS)核心数据库,运用CiteSpace文献计量软件对该研究领域进行了全面的梳理,从多个角度分析生猪产业低碳发展现状,并揭示该领域研究热点的演变以及未来发展趋势。结果:低碳养猪研究的发展依次经历了3个时期和4个产业发展阶段,其中气体控制与资源高效利用两个主题在研究的各时期均表现出较高热度;核心作者和机构合作网络已初步形成,李荣华、Awasthi、Lehmann、Sommer等是该领域研究较有影响力的学者,中国和美国是该领域发文最多的国家;研究确定了87个关键词、4个研究热点和5个研究领域,并绘制了生猪产业低碳发展研究知识路线图。未来研究将继续注重技术创新、加强跨学科间的合作,并在此基础上,进一步应用跨学科方法开展生猪生产效率与动物福利、养殖主体低碳行为决策等前沿研究。同时,政府的引导能够让生猪产业降碳减排潜力得到更好地量化。