arXiv - ECON - Econometrics最新文献_第3页

DEPLOYERS: An agent based modeling tool for multi country real world data DEPLOYERS：基于代理的多国真实世界数据建模工具

arXiv - ECON - Econometrics Pub Date : 2024-09-07 DOI: arxiv-2409.04876

Martin Jaraiz, Ruth Pinacho

{"title":"DEPLOYERS: An agent based modeling tool for multi country real world data","authors":"Martin Jaraiz, Ruth Pinacho","doi":"arxiv-2409.04876","DOIUrl":"https://doi.org/arxiv-2409.04876","url":null,"abstract":"We present recent progress in the design and development of DEPLOYERS, an\u0000agent-based macroeconomics modeling (ABM) framework, capable to deploy and\u0000simulate a full economic system (individual workers, goods and services firms,\u0000government, central and private banks, financial market, external sectors)\u0000whose structure and activity analysis reproduce the desired calibration data,\u0000that can be, for example a Social Accounting Matrix (SAM) or a Supply-Use Table\u0000(SUT) or an Input-Output Table (IOT).Here we extend our previous work to a\u0000multi-country version and show an example using data from a 46-countries\u000064-sectors FIGARO Inter-Country IOT. The simulation of each country runs on a\u0000separate thread or CPU core to simulate the activity of one step (month, week,\u0000or day) and then interacts (updates imports, exports, transfer) with that\u0000country's foreign partners, and proceeds to the next step. This interaction can\u0000be chosen to be aggregated (a single row and column IO account) or\u0000disaggregated (64 rows and columns) with each partner. A typical run simulates\u0000thousands of individuals and firms engaged in their monthly activity and then\u0000records the results, much like a survey of the country's economic system. This\u0000data can then be subjected to, for example, an Input-Output analysis to find\u0000out the sources of observed stylized effects as a function of time in the\u0000detailed and realistic modeling environment that can be easily implemented in\u0000an ABM framework.","PeriodicalId":501293,"journal":{"name":"arXiv - ECON - Econometrics","volume":"178 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving the Finite Sample Performance of Double/Debiased Machine Learning with Propensity Score Calibration 利用倾向得分校准提高双重/偏差机器学习的有限样本性能

arXiv - ECON - Econometrics Pub Date : 2024-09-07 DOI: arxiv-2409.04874

Daniele Ballinari, Nora Bearth

{"title":"Improving the Finite Sample Performance of Double/Debiased Machine Learning with Propensity Score Calibration","authors":"Daniele Ballinari, Nora Bearth","doi":"arxiv-2409.04874","DOIUrl":"https://doi.org/arxiv-2409.04874","url":null,"abstract":"Machine learning techniques are widely used for estimating causal effects.\u0000Double/debiased machine learning (DML) (Chernozhukov et al., 2018) uses a\u0000double-robust score function that relies on the prediction of nuisance\u0000functions, such as the propensity score, which is the probability of treatment\u0000assignment conditional on covariates. Estimators relying on double-robust score\u0000functions are highly sensitive to errors in propensity score predictions.\u0000Machine learners increase the severity of this problem as they tend to over- or\u0000underestimate these probabilities. Several calibration approaches have been\u0000proposed to improve probabilistic forecasts of machine learners. This paper\u0000investigates the use of probability calibration approaches within the DML\u0000framework. Simulation results demonstrate that calibrating propensity scores\u0000may significantly reduces the root mean squared error of DML estimates of the\u0000average treatment effect in finite samples. We showcase it in an empirical\u0000example and provide conditions under which calibration does not alter the\u0000asymptotic properties of the DML estimator.","PeriodicalId":501293,"journal":{"name":"arXiv - ECON - Econometrics","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lee Bounds with Multilayered Sample Selection 多层样本选择的李氏限界

arXiv - ECON - Econometrics Pub Date : 2024-09-06 DOI: arxiv-2409.04589

Kory Kroft, Ismael Mourifié, Atom Vayalinkal

{"title":"Lee Bounds with Multilayered Sample Selection","authors":"Kory Kroft, Ismael Mourifié, Atom Vayalinkal","doi":"arxiv-2409.04589","DOIUrl":"https://doi.org/arxiv-2409.04589","url":null,"abstract":"This paper investigates the causal effect of job training on wage rates in\u0000the presence of firm heterogeneity. When training affects worker sorting to\u0000firms, sample selection is no longer binary but is \"multilayered\". This paper\u0000extends the canonical Heckman (1979) sample selection model - which assumes\u0000selection is binary - to a setting where it is multilayered, and shows that in\u0000this setting Lee bounds set identifies a total effect that combines a\u0000weighted-average of the causal effect of job training on wage rates across\u0000firms with a weighted-average of the contrast in wages between different firms\u0000for a fixed level of training. Thus, Lee bounds set identifies a\u0000policy-relevant estimand only when firms pay homogeneous wages and/or when job\u0000training does not affect worker sorting across firms. We derive sharp\u0000closed-form bounds for the causal effect of job training on wage rates at each\u0000firm which leverage information on firm-specific wages. We illustrate our\u0000partial identification approach with an empirical application to the Job Corps\u0000Study. Results show that while conventional Lee bounds are strictly positive,\u0000our within-firm bounds include 0 showing that canonical Lee bounds may be\u0000capturing a pure sorting effect of job training.","PeriodicalId":501293,"journal":{"name":"arXiv - ECON - Econometrics","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An MPEC Estimator for the Sequential Search Model 顺序搜索模型的 MPEC 估算器

arXiv - ECON - Econometrics Pub Date : 2024-09-06 DOI: arxiv-2409.04378

Shinji Koiso, Suguru Otani

引用次数: 0

Extreme Quantile Treatment Effects under Endogeneity: Evaluating Policy Effects for the Most Vulnerable Individuals 内生性下的极端量化治疗效应：评估针对最弱势个体的政策效应

arXiv - ECON - Econometrics Pub Date : 2024-09-06 DOI: arxiv-2409.03979

Yuya Sasaki, Yulong Wang

引用次数: 0

Performance of Empirical Risk Minimization For Principal Component Regression 主成分回归的经验风险最小化性能

arXiv - ECON - Econometrics Pub Date : 2024-09-05 DOI: arxiv-2409.03606

Christian Brownlees, Guðmundur Stefán Guðmundsson, Yaping Wang

引用次数: 0

Automatic Pricing and Replenishment Strategies for Vegetable Products Based on Data Analysis and Nonlinear Programming 基于数据分析和非线性编程的蔬菜产品自动定价和补货策略

arXiv - ECON - Econometrics Pub Date : 2024-09-05 DOI: arxiv-2409.09065

Mingpu Ma

{"title":"Automatic Pricing and Replenishment Strategies for Vegetable Products Based on Data Analysis and Nonlinear Programming","authors":"Mingpu Ma","doi":"arxiv-2409.09065","DOIUrl":"https://doi.org/arxiv-2409.09065","url":null,"abstract":"In the field of fresh produce retail, vegetables generally have a relatively\u0000limited shelf life, and their quality deteriorates with time. Most vegetable\u0000varieties, if not sold on the day of delivery, become difficult to sell the\u0000following day. Therefore, retailers usually perform daily quantitative\u0000replenishment based on historical sales data and demand conditions. Vegetable\u0000pricing typically uses a \"cost-plus pricing\" method, with retailers often\u0000discounting products affected by transportation loss and quality decline. In\u0000this context, reliable market demand analysis is crucial as it directly impacts\u0000replenishment and pricing decisions. Given the limited retail space, a rational\u0000sales mix becomes essential. This paper first uses data analysis and\u0000visualization techniques to examine the distribution patterns and\u0000interrelationships of vegetable sales quantities by category and individual\u0000item, based on provided data on vegetable types, sales records, wholesale\u0000prices, and recent loss rates. Next, it constructs a functional relationship\u0000between total sales volume and cost-plus pricing for vegetable categories,\u0000forecasts future wholesale prices using the ARIMA model, and establishes a\u0000sales profit function and constraints. A nonlinear programming model is then\u0000developed and solved to provide daily replenishment quantities and pricing\u0000strategies for each vegetable category for the upcoming week. Further, we\u0000optimize the profit function and constraints based on the actual sales\u0000conditions and requirements, providing replenishment quantities and pricing\u0000strategies for individual items on July 1 to maximize retail profit. Finally,\u0000to better formulate replenishment and pricing decisions for vegetable products,\u0000we discuss and forecast the data that retailers need to collect and analyses\u0000how the collected data can be applied to the above issues.","PeriodicalId":501293,"journal":{"name":"arXiv - ECON - Econometrics","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142261058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Momentum Dynamics in Competitive Sports: A Multi-Model Analysis Using TOPSIS and Logistic Regression 竞技体育中的动量动态：使用 TOPSIS 和 Logistic 回归的多模型分析

arXiv - ECON - Econometrics Pub Date : 2024-09-04 DOI: arxiv-2409.02872

Mingpu Ma

引用次数: 0

The Impact of Data Elements on Narrowing the Urban-Rural Consumption Gap in China: Mechanisms and Policy Analysis 数据要素对缩小中国城乡消费差距的影响：机制与政策分析

arXiv - ECON - Econometrics Pub Date : 2024-09-04 DOI: arxiv-2409.02662

Mingpu Ma

{"title":"The Impact of Data Elements on Narrowing the Urban-Rural Consumption Gap in China: Mechanisms and Policy Analysis","authors":"Mingpu Ma","doi":"arxiv-2409.02662","DOIUrl":"https://doi.org/arxiv-2409.02662","url":null,"abstract":"The urban-rural consumption gap, as one of the important indicators in social\u0000development, directly reflects the imbalance in urban and rural economic and\u0000social development. Data elements, as an important component of New Quality\u0000Productivity, are of significant importance in promoting economic development\u0000and improving people's living standards in the information age. This study,\u0000through the analysis of fixed-effects regression models, system GMM regression\u0000models, and the intermediate effect model, found that the development level of\u0000data elements to some extent promotes the narrowing of the urban-rural\u0000consumption gap. At the same time, the intermediate variable of urban-rural\u0000income gap plays an important role between data elements and consumption gap,\u0000with a significant intermediate effect. The results of the study indicate that\u0000the advancement of data elements can promote the balance of urban and rural\u0000residents' consumption levels by reducing the urban-rural income gap, providing\u0000theoretical support and policy recommendations for achieving common prosperity\u0000and promoting coordinated urban-rural development. Building upon this, this\u0000paper emphasizes the complex correlation between the development of data\u0000elements and the urban-rural consumption gap, and puts forward policy\u0000suggestions such as promoting the development of the data element market,\u0000strengthening the construction of the digital economy and e-commerce, and\u0000promoting integrated urban-rural development. Overall, the development of data\u0000elements is not only an important path to reducing the urban-rural consumption\u0000gap but also one of the key drivers for promoting the balanced development of\u0000China's economic and social development. This study has a certain theoretical\u0000and practical significance for understanding the mechanism of the urban-rural\u0000consumption gap and improving policies for urban-rural economic development.","PeriodicalId":501293,"journal":{"name":"arXiv - ECON - Econometrics","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fitting an Equation to Data Impartially 不偏不倚地根据数据拟合方程

arXiv - ECON - Econometrics Pub Date : 2024-09-04 DOI: arxiv-2409.02573

Chris Tofallis

{"title":"Fitting an Equation to Data Impartially","authors":"Chris Tofallis","doi":"arxiv-2409.02573","DOIUrl":"https://doi.org/arxiv-2409.02573","url":null,"abstract":"We consider the problem of fitting a relationship (e.g. a potential\u0000scientific law) to data involving multiple variables. Ordinary (least squares)\u0000regression is not suitable for this because the estimated relationship will\u0000differ according to which variable is chosen as being dependent, and the\u0000dependent variable is unrealistically assumed to be the only variable which has\u0000any measurement error (noise). We present a very general method for estimating\u0000a linear functional relationship between multiple noisy variables, which are\u0000treated impartially, i.e. no distinction between dependent and independent\u0000variables. The data are not assumed to follow any distribution, but all\u0000variables are treated as being equally reliable. Our approach extends the\u0000geometric mean functional relationship to multiple dimensions. This is\u0000especially useful with variables measured in different units, as it is\u0000naturally scale-invariant, whereas orthogonal regression is not. This is\u0000because our approach is not based on minimizing distances, but on the symmetric\u0000concept of correlation. The estimated coefficients are easily obtained from the\u0000covariances or correlations, and correspond to geometric means of associated\u0000least squares coefficients. The ease of calculation will hopefully allow\u0000widespread application of impartial fitting to estimate relationships in a\u0000neutral way.","PeriodicalId":501293,"journal":{"name":"arXiv - ECON - Econometrics","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142184141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0