analysis and application of demand forecasting model with multi element variable parameters

A forecasting model for logistics demand was presented to overcome the limitations of single goal forecasts of logistics demand and forecast data complexity. Based on the forecasting evaluation index and pretreatment of rough set theory, a multi input and multi output wavelet network (MMWNN) model for forecasting multi element regional logistics demand was studied. The network configuration was confirmed using the stepwise checkout and iterative gradient descent methods. After rough set reduction, the evaluation index was used to forecast the multi element regional logistics demand. The results of the numerical example indicate the feasibility and effectiveness of the model.     

Regional Indexes of Leading Indicators: An Evaluation Of Forecasting Performance

ABSTRACT Indexes of leading indicators are used to forecast short-run changes in economic activity in many states and metropolitan areas. This article examines the forecasting performance of a sample of such regional indexes over several business cycles. Although these indexes vary across regions, the results show that they do provide forecasts of recessions and recoveries and also exhibit some potential for forecasting quantitative changes in regional employment.     

Improving Local Manufacturing Employment Forecasts Using Cointegration Analysis

Procedures for tracking and forecasting economic conditions in regional economies have evolved significantly over the last 30 years. Much of this evolution has followed developments in macroeconomics, where techniques for tracking/forecasting key economic variables have tended to originate. This technique adoption and adaptation process continues today, as developments in the technique adoption and adaptation process continues today, as developments in the modeling of cointegrated macroeconomic time series have begun to appear in the regional modeling and forecasting literature. This paper presents an effort at modeling a segment of a regional economy using the cointegration testing procedures suggested by Johansen and Jusilius (1990) to develop a forecasting model for manufacturing employment in Milwaukee, WI. The paper demonstrates how Vector Error Correction (VEC) modeling can lead to gains in the accuracy of local manufacturing employment forecasts relative to more traditional VAR models in either levels or first-differenced form. In the process, it demonstrates procedures for developing a relatively simple VEC model that reveals something about the structure of the local manufacturing sector, including possible linkages to the national economy. This information can assist local policy makers in anticipating and adapting to business cycle-related fluctuations in this critical sector of the local economy.     

Maquiladora Employment Dynamics in Nuevo Laredo

ABSTRACT The Nuevo Laredo maquiladora sector has grown enormously during the last two decades. The short‐term time series characteristics of this portion of the regional economy are analyzed in an attempt to quantify the trends underlying this remarkable performance. Parameter estimation is accomplished via linear transfer function (LTF) analysis. Data are drawn from the January 1990–December 2000 sample period. Empirical results indicate that real wage rates, maquiladora plants, U.S. industrial activity, and the real exchange rate of the peso play significant roles in determining month‐to‐month fluctuations in maquiladora employment. Furthermore, sub‐sample forecast simulation exercises are conducted as an additional means for verifying model reliability. Empirical results indicate that the forecasts generated with the LTF model are less accurate than those associated with a simple random walk procedure for twelve separate step‐length periods.     

Short-Term Electric Load Forecasting Based Trends Combination Model

In short term load forecasting based on ANN,weather is one of the important factors which impacts on load greatly. In order to capture the effect of weather on load, this paper presents a novel thought based on ANN and trends combination short term load forecasting. Decompose the underlying relationships between load and weather variables into three main trends of weekly, daily and hourly. Three separated ANNs capture each trend. Another ANN to arrive at the final forecast combines the forecasts yielded by individual ANNs. The performances of the proposed model and the traditional model are compared on the basis of one week ahead hourly forecasts. Results indicate that the proposed ANN based model can achieve greater forecasting accuracy than the traditional ANN based model.     

Vacancy Dynamics and Labor Market Efficiency in the Dutch Labor Market

ABSTRACT This paper focuses on cyclical and regional variations in vacancy dynamics in labor markets with persistent imbalances between demand and supply. In particular the so-called matching approach is used to investigate labor market efficiency across regions and over the business cycle. In this matching approach the relationship between the flow of filled vacancies and regional stocks of unemployed job seekers and vacant jobs is specified in a “search production” function. The matching approach is applied to the Dutch labor market, which is characterized by strong disequilibria and persistent regional differences in unemployment and vacancy rates. To explore the development of these regional imbalances from a demand side perspective, the dynamic structure of regional data on vacancies is analyzed over the business cycle. The movements of vacancy duration and the change in the vacancy stock over time appear to be similar across Dutch regions. Moreover, an investigation of the structural causes of regional variations in vacancy duration via shift-share analysis makes clear that regional differences in sectoral composition of unfilled vacancies do not contribute to regional differences in vacancy duration in the period 1989–93. Estimation results of a matching model reveal that there are no region-specific differences in labor market efficiency to produce filled vacancies. The ratio of vacancies to unemployment appears to be the critical determinant of the matching process in the Dutch regions. Another general (non region-specific) finding is that the estimated labor market efficiency increases during recessionary and recovery periods while it decreases during an economic boom.     

农业气象服务满意度测评方法研究

为了深入了解农户对农业气象服务的需求,有效地避免和降低气象灾害及次生灾害带来的危害和损失,真正发挥农业气象服务的作用,结合研究当地农业气象服务的特点,构建农业气象服务用户满意度测度模型(CSIAS),通过数学方法计算出农业气象服务用户对农业气象服务的满意度指数,分析用户对农业气象服务的需求结构。应用满意度测度模型,结合2015 年武威市农业气象服务满意度调查问卷进行实例分析。结果显示,用户对当地农业气象服务满意度比较高,将来对气象服务产品继续保持较高的关注度,但是对于天气预报准确率,尤其是灾害性天气预报的准确率满意度较低,这就要求气象部门在提高天气预报准确率这方面还需努力。此次农业气象服务满意度评价,使气象部门能够合理地确定服务产品重点,找出为农服务产品中的不足,改进服务内容,为今后农业气象服务工作的改进奠定结实的基础。     

A Community Economic Forecasting and Simulation System: Description of a Satellite Model

This paper deals with the problem of modelling sub-county areas that are so small that county level forecasts cannot be used for policy purposes. Starting from a simple specification that relates demand for local goods and services to local and non-local income, a system of equations is developed that can be used as a satellite to a county model to forecast impacts of economic events at the town level. Regression coefficients for the equations are estimated using data at the one-digit SIC code level for a pooled sample of towns in Massachusetts. Model validation tests are reported. An example of an application is provided by simulating impacts of 500 new manufacturing jobs in a town within a county. Our approach yields simulation and forecasting results for both the town and the county.     

多个数值预报产品对山西3次强降水过程预报性能的对比分析

为更好地释用数值模式的预报产品,采用客观分析和ETS评分方法,运用T639-thin模式、ECMWF-thin模式、Japan_thin模式及NECP模式对2014年7月发生在山西的3次降水过程的预报性能进行了效果检验和对比分析。分析结果表明：4家模式对欧亚大陆中高纬环流形式以及地面系统的调整和演变均有较强的预报能力;4家数值模式预报产品基本能把握雨带的走向,但对强降水过程中降水强度的模拟与实况相比偏差较大,而且对强降水中心的预报稳定性也较差;对于ETS评分,NECP模式的评分在3次过程中均较高,并且不同数值模式的24 h时效预报效果要优于其他预报时效。总体来看,对于环流形式的演变,EC模式模拟效果是最好的,其次是NECP模式,T639模式和日本模式次之;对于降水量级以及落区的预报,NECP模式预报较准确,具有较高的参考价值,其次是EC模式,而T639模式和日本模式预报的稳定性较差。     

Can State Tax Policy Increase Economic Activity and Reduce Inequality?

Previous research shows that when changes in national commodity and income tax rates affect labor supply decisions differently, relative rates can be altered to increase welfare. In the U.S., 40 states impose both a sales and income tax; however, the reliance varies widely. This paper uses a computable general equilibrium model to examine tax policy changes in Colorado. The findings suggest that the revenue neutral changes to income and sales tax rates can affect both the level of economic activity and the distribution of income. When labor force participation is highly sensitive to income tax rate changes—which this paper suggests is the case—progressive changes to Colorado's tax policy changes can both reduce inequality and increase output and employment.     

Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment

In recent years, maize has become one of the main alternative crops for the Autumn–Winter growing season (off-season) in several regions of Brazil. Water deficits, sub-optimum temperatures and low solar radiation levels are some of the more common problems that are experienced during this growing season. However, the impact of variable weather conditions on crop production can be analyzed with crop simulation models. The objectives of this study were to evaluate the Cropping System Model (CSM)-CERES-Maize for its ability to simulate growth, development, grain yield for four different maturity maize hybrids grown off-season in a subtropical region of Brazil, to study the impact of different planting dates on maize performance under rainfed and irrigated conditions, and for yield forecasting for the most common off-season production system. The CSM-CERES-Maize model was evaluated with experimental data collected during three field experiments conducted in Piracicaba, SP, Brazil. The experiments were completely randomized with three replications for the 2001 experiment and four replications for the 2002 experiments. For the yield forecasting application, daily weather data for 2002 were used until the forecast date, complemented with 25 years of historical daily weather data for the remainder of the growing season. Six planting dates were simulated, starting on February 1 and repeated every 15 days until April 15. The evaluation of the CSM-CERES-Maize showed that the model was able to simulate phenology and grain yield for the four hybrids accurately, with normalized RMSE (expressed in percentage) less than 15%. The planting date analysis showed that a delayed planting date from February 1 to April 15 caused a decrease in average yield of 55% for the rainfed and 21% for the irrigated conditions for all hybrids. The yield forecasting analysis demonstrated that an accurate yield forecast could be provided at approximately 45 days prior to the harvest date for all four maize hybrids. These results are promising for farmers and decision makers, as they could have access to accurate yield forecasts prior to final harvest. However, to be able to make practical decisions for stock management of maize grains, it is necessary to develop this methodology for different locations. Future model evaluations might also be needed due to the release of new cultivars by breeders.     

Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment

In recent years, maize has become one of the main alternative crops for the Autumn–Winter growing season (off-season) in several regions of Brazil. Water deficits, sub-optimum temperatures and low solar radiation levels are some of the more common problems that are experienced during this growing season. However, the impact of variable weather conditions on crop production can be analyzed with crop simulation models. The objectives of this study were to evaluate the Cropping System Model (CSM)-CERES-Maize for its ability to simulate growth, development, grain yield for four different maturity maize hybrids grown off-season in a subtropical region of Brazil, to study the impact of different planting dates on maize performance under rainfed and irrigated conditions, and for yield forecasting for the most common off-season production system. The CSM-CERES-Maize model was evaluated with experimental data collected during three field experiments conducted in Piracicaba, SP, Brazil. The experiments were completely randomized with three replications for the 2001 experiment and four replications for the 2002 experiments. For the yield forecasting application, daily weather data for 2002 were used until the forecast date, complemented with 25 years of historical daily weather data for the remainder of the growing season. Six planting dates were simulated, starting on February 1 and repeated every 15 days until April 15. The evaluation of the CSM-CERES-Maize showed that the model was able to simulate phenology and grain yield for the four hybrids accurately, with normalized RMSE (expressed in percentage) less than 15%. The planting date analysis showed that a delayed planting date from February 1 to April 15 caused a decrease in average yield of 55% for the rainfed and 21% for the irrigated conditions for all hybrids. The yield forecasting analysis demonstrated that an accurate yield forecast could be provided at approximately 45 days prior to the harvest date for all four maize hybrids. These results are promising for farmers and decision makers, as they could have access to accurate yield forecasts prior to final harvest. However, to be able to make practical decisions for stock management of maize grains, it is necessary to develop this methodology for different locations. Future model evaluations might also be needed due to the release of new cultivars by breeders.     

福建省晋江市农村劳动力就业现况分析

农村劳动力外出就业是当前农村劳动力转移主要方式。福建省晋江市作为沿海较发达地区的代表,在农村劳动力转移就业方面有自身特点。本文在对晋江市进行实地调研的基础上,探寻了晋江市自身用工方面特点、缺工原因、未来用工走势及应因对策等。晋江市用工特点为用工量大、结构性缺工严重等,缺工原因在于农村剩余劳动力再转移可能性小、产业不断扩大升级以及劳动力市场供过于求带来选择性就业等,而未来用工走势近期来看还将是用工短缺扩大化以及长远来看技术进步后用工短缺现象的进一步缓和,政府将在涉及建立健全就业服务体系、加大培训力度、开展劳务协作等方面采取措施,企业也将就提高就业人员的待遇并使其对将要或已经就业岗位有较好的预期外,积极推进技术改造。     

局域法邻近点选取对供水量预测精度的影响

混沌局域法预测模型适用于非线性、非平稳的城市日供水量预测,而邻近相点个数的选取对该模型预测精度有直接影响。传统方法通常以嵌入维m作为参考值,凭经验选取m+1个邻近相点,且仅使用欧式距离法计算当前相点距离,无法反映相点的运动趋势,易引入伪邻近相点,导致预测精度的降低。鉴于此,将演化追踪法引入城市日供水量预测,通过挖掘邻近相点的历史演化规律对参考样本进行优选,以提高预测精度。最后,采用实际日供水量数据验证所提出方法,结果表明,运用演化追踪法优选邻近相点能显著提高日供水量预测精度,预测平均绝对误差由2.501%降低到1.683%。     

Taxation of Natural Resources and State Economic Growth

The econometric evidence that has been brought to bear on the question of how state and local taxes affect the location decision of firms among competing states or regions is surprisingly sparse and often contradictory. In this research the question is addressed from a different empirical perspective than has been considered heretofore. Using a pool of cross-section and time-series data, the trends in employment and capital formation in three energy-rich states are analyzed during a period when these states substituted energy-related revenues for more traditional forms of taxation. McLure's general equilibrium model of regional taxation and industrial location forms the theoretical basis for the empirical analysis. The findings suggest that relative changes in state and local taxes on products and labor are of more significance as a location determinant than relative changes in the state corporate income tax.     

基于分数阶灰色模型的生鲜电商产品销量预测研究

新型冠状病毒的爆发,使供应链受到了不良影响,蔬菜水果等生鲜商品线下批发零售受阻,生鲜电商却迎来了新一轮的发展.从生鲜消费者角度出发,通过构建分数阶灰色预测模型对生鲜产品的需求量进行预测,并引入甘福园生鲜电商销售数据进行验证,得到柠檬、车厘子、苹果及火龙果4种水果拟合值的平均绝对百分比误差(MAPE)分别为8.61％、7.15％、7.16％、6.81％,其值均小于灰色预测模型和一次指数平滑法,且由该模型得到预测值的平均绝对百分比误差均小于10％,结果表明该模型适用于生鲜电商产品销量预测.     

中国水稻稻纵卷叶螟区域气象等级预测模型

为了建立水稻不同区域、不同生育期的水稻稻纵卷叶螟预测模型,利用103个植保站2000-2014年稻纵卷叶螟虫情资料与气象资料,采用SPSS软件进行相关分析与主成分分析,在逐步回归的基础上建立水稻稻纵卷叶螟不同区域、不同生育期的发生发展气象等级与迁入气象等级预测模型。结果表明：以华南早稻为例,影响早稻移栽分蘖期发生发展的关键因子包括3月下旬累积降水量、4月上旬平均气温、4月下旬平均气温、5月上旬平均气温以及5月上旬最高气温＞30℃天数;迁飞的关键因子包括4月平均相对湿度、3月下旬平均气温、3月下旬平均相对湿度以及4月上旬平均日照时数。通过2000—2012年数据回代检验发现,不同水稻种植区移栽分蘖期和抽穗开花期发生发展气象等级平均准确率能达到80%以上,迁入气象等级在85%以上。通过2013—2014年外推预报时,发生发展气象等级平均准确率在80%以上,迁入气象等级在78%以上;当预测站点样本数较少时,预报的准确率普遍下降,西南一季稻下降明显。预测模型可从气象角度对中国水稻稻纵卷叶螟发生发展和迁入进行预测。     

The Impact of Output and Productivity Changes on Manufacturing Employment

Traditional univariate shift-share studies of employment provide an unreliable indicator of the relative performance of a region or an industry for they fail to separate the effects of output and productivity change on the demand for labor. An extended shift-share model is proposed that overcomes this weakness and permits identification of different processes of regional development. This model is used to investigate annual employment change in twenty (two-digit SIC) manufacturing industries in nine census regions of the U.S. between 1950 and 1986. The timing and depth of the exodus of manufacturing jobs from the snowbelt to the sunbelt is illustrated along with the business cycle performance of industries and regions. Productivity growth in the sunbelt is positively associated with rapid output expansion, whereas in the snowbelt it is associated with the loss of market share and economic rationalization.     

The Future of State and Local Economic Development Policy: What Research Is Needed

Research will be more relevant to state and local economic development policy if this research focuses on research gaps. One gap is better estimates of how local labor demand policies affect local jobs. A second gap is better understanding of how labor supply policies affect overall local labor market outcomes, adjusting for spillovers and displacement. A third gap is better understanding of how effects of local employment shocks vary with local labor market conditions.