二三产业产值与劳动力需求关系及预测研究

发布时间：2018-01-04 22:24

本文关键词：二三产业产值与劳动力需求关系及预测研究　出处：《东北农业大学》2013年硕士论文　论文类型：学位论文

【摘要】：改革开放30多年以来，我国各方面取得了辉煌的成就。国内生产总值（GDP）保持快速增长趋势。我国的产业结构和就业结构随着改革开放、经济的发展也随之发生了相应的变化。但是我国的当代经济发展与人口资源、环境并不是很协调，劳动力资源配置在经济和政治上都具有极其重要的位置。劳动力资源配置的方式、机制不仅影响劳动力自身利用效率，而且还对整个社会经济运作的效率产生影响，它是经济过程中的一个基本要素。在当今社会主义市场中，经济要快速健康的发展，劳动力资源的配置显得格外的重要。在我国经济快速发展的同时带动了产业结构的调整，产业结构与就业结构息息相关，随之带动了劳动力结构的调整。我国是个农业大国，由此产生的大批量劳动力的转移将对我国的经济腾飞产生巨大的挑战，探讨、分析中国产业结构调整对劳动力配置的影响具有实际的现实意义。本文首先采用定量分析的方法，分析了我国产业结构及其劳动力需求现状。收集了我国从1981年至2010年近三十年的国内生产总值与就业人员数据，用于定量研究。主要方法用到了相关分析、回归分析、BP神经网络及其组合预测等数理统计和神经网络等理论知识。以Maltlab、SPSS17.0等为运算工具。本文主要对标准BP神经网络时间序列预测问题做了分析，并且根据研究需要，提出了适合本研究的基于改进的BP神经网络时间序列预测模型；用一元回归进行了第二三产业产值与劳动力需求的相关性分析，在得出二三产业产值与劳动力需求回归方程，并通过假设检验；将改进的BP神经网络时间序列预测及其以误差绝对值最小为目标的组合预测应用于第二三产业产值的预测，得出基于改进的BP神经网络时间序列预测模型优于组合预测模型，以改进的BP神经网络时间序列预测模型得到的产值代入回归分析得出的回归方程，预测出劳动力需求量。本文总共分为六大章节：第一章是引言部分，主要介绍了本文研究的背景，国内外研究现状及其本文所用到的方法和本文所研究的主要内容以及技术路线图；第二章为理论概念界定和本文研究的理论基础介绍，概念界定部分主要介绍了产业、产业结构、产值、劳动力、劳动力需求、预测、预测分类等概念，，回归分析、神经网络的相关概念及其模型以及组合预测模型；第三章主要在基于BP神经网络时间序列预测问题分析的基础上，提出了适合本研究的基于改进的BP神经网络时间序列预测模型，并对其模型进行了阐述；第四章，在相关性分析基础上，做了回归分析，利用对数回归模型，得出二三产业产值与劳动力需求的数学回归模型，并通过了假设检验；第五章分为产值预测和劳动力需求两部分，产值预测又分为基于改进的BP神经网络时间序列预测与组合预测两个模型，在产值预测的基础上，预测出劳动力需求量；第六章为本文的结论。
[Abstract]:Since 30 years of reform and opening up, the various aspects of our country has made brilliant achievements. The gross domestic product (GDP) to maintain a rapid growth trend. The industrial structure and employment structure in our country with the reform and opening up, economic development has changed accordingly. But China's contemporary economic development and population, resources, environment and not well, the allocation of labor resources has the extremely important position in economy and politics. The allocation of labor resources, the mechanism not only affects labor efficiency, but also affect the entire social and economic operation of the production efficiency, it is one of the basic elements of the economic process. In today's socialist market economy. The rapid and healthy development, the allocation of labor resources is particularly important. In the rapid development of China's economy and promote the adjustment of industrial structure, industrial structure and employment structure information Relevant information, will be driven by the adjustment of the labor structure. China is a large agricultural country, resulting in the transfer of large quantities of labor will have a huge challenge to the economy of our country to explore the practical significance, analysis of the impact of Chinese industrial structure adjustment on labor force allocation with the actual.
This paper adopts the method of quantitative analysis, analyzes the current situation of China's industrial structure and labor demand. Collection of China's GDP and employment data from 1981 to 2010 for nearly thirty years, for the quantitative study. The main methods used in the correlation analysis, regression analysis, BP neural network and its combination forecasting and mathematical statistics the neural network theory. Based on Maltlab, SPSS17.0 as the calculation tool. This paper mainly analyzes the prediction problem of standard BP neural network, time series, and according to the research needs, the paper proposes the research based on BP neural network time series forecasting model of improved; analyzed the relativity of the two or three industrial output and labor demand by regression, the two or three industry output value and labor demand regression equation, and through hypothesis test; the improved BP neural network time series In order to forecast and forecast error minimum absolute value of combination forecasting is applied in the two or three industrial output, the BP neural network time series forecasting model of improved superior combination forecasting model based on regression equation regression analysis with BP neural network time series forecasting value into the model improved the forecast, labor demand.
This paper is divided into six chapters: the first chapter is the introduction part, mainly introduces the background, main contents and the status quo and the method used by the domestic and foreign research institute and technology roadmap; the second chapter is theoretical basis for defining the concept and the introduction part mainly introduces the definition, industry, industrial structure, output, labor, labor demand, forecast, forecast classification concepts, regression analysis, neural network model and its related concepts and combination forecasting model; in the third chapter, based on the BP neural network time series prediction problem based on the analysis, the paper proposes the research on the prediction model of BP neural network time series based on the improved, and the models were discussed; the fourth chapter, the correlation analysis based on the regression analysis, using the logarithmic regression model, the Two or three industrial output and labor demand mathematical regression model, and through the hypothesis test; the fifth chapter is divided into two parts to forecast the output value and labor demand, output prediction is divided into BP neural network time series prediction combined with improved prediction based on two models based on output forecast, forecast of labor demand; the sixth chapter is the conclusion of this paper.

【学位授予单位】：东北农业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：F124.1;F249.21

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