我国人均国内生产总值的时间序列分析(1952-2011)与静态预测(2012-2015)

国内生产总值是最重要的宏观经济指标,人均国内生产总值是衡量国家发展程度与人民生活水平的重要标志。党的十八大报告提出到2020年全面建成小康社会,实现GDP和人均收入比2010年翻一番的目标,因此对我国人均国内生产总值进行时间序列分析与静态预测对实现GDP总量翻番的目标具有重要意义。文章从国内生产总值和时间序列模型的基本理论出发,选取了自1952年至2011年人均GDP的60个样本数据,建立了以时间序列为基础的AR(1)模型,模型通过了EViews软件中的所有检验,模型的精度较高。文章利用AR(1)模型对2012年至2015年的人均GDP做出了预测,预测结果表明,至"十二五"期末,我国的名义人均GDP基本可实现比2010年翻一番的目标。     

基于ARMA模型的上海市人均GDP时间序列分析与预测

本文分析了上海市人均GDP水平时间序列(1978年至2008年),在将数据平稳化的基础上建立自回归移动平均模型(ARMA模型),从中找出上海市人均GDP序列变化的规律,并在此基础上对未来几年的指标数值进行了预测。     

基于ARMA模型的上海市人均GDP时间序列分析与预测

本文分析了上海市人均GDP水平时间序列（1978年至2008年）,在将数据平稳化的基础上建立自回归移动平均模型（ARMA模型）,从中找出上海市人均GDP序列变化的规律,并在此基础上对未来几年的指标数值进行了预测。     

中国人均GDP时间序列模型建模研究

本文对中国人均GDP1949年至2004年时间序列进行研究,建立了用于预测的时间序列模型,结果为ARIMA(1,2,1)。     

山东省人均GDP时间序列模型的建立

人均GDP的增长具有其内在的规律性。从山东省的实际情况出发,以1978--2002年山东省逐年人均GDP的统计数据为依据,将这些数据进行平稳化、零均值化处理,并利用序列的自相关函数、偏自相关函数的性质,确认序列应当适合的模型,从而建立其时间序列模型。     

基于时间序列的郑州市人均生产总值的预测

随着社会经济的不断发展、生活水平的提高及人口的增加,通过GDP这一宽泛的指标来反映一个地区经济的发展状况是不准确的。由于GDP不能很准确地反映平均每个人的生活水平,而人均GDP则能弥补GDP的这点不足。因为人均GDP=总产出/总人口,它是一个既考虑经济总量大小又考虑人口数量因素的综合性指标,所以常常用来了解和把握一个国家或者地区的宏观经济运行状况、发展水平和人民生活水准。所以论文利用ARIMA模型对人均生产总值进行短期的预测。     

我国农村居民人均生活消费现金支出的预测分析

"三农"问题的核心是农民问题,农民问题的核心是增收问题,本文对衡量农民收入的重要变量:我国农村居民人均生活消费现金支出进行时间序列预测分析,研究其发展有助于农村政策的制定。本文收集到1990-2011年的我国农村居民人均生活消费现金支出季度数据,将这些数据进行平稳化、零均值处理,并利用序列的自相关及偏相关函数的性质,确认数据所适合的模型,从而建立了时间序列模型并对其进行分析。     

我国农村居民人均生活消费现金支出的预测分析

"三农"问题的核心是农民问题,农民问题的核心是增收问题,本文对衡量农民收入的重要变量:我国农村居民人均生活消费现金支出进行时间序列预测分析,研究其发展有助于农村政策的制定。本文收集到1990-2011年的我国农村居民人均生活消费现金支出季度数据,将这些数据进行平稳化、零均值处理,并利用序列的自相关及偏相关函数的性质,确认数据所适合的模型,从而建立了时间序列模型并对其进行分析。     

湖北省农村居民人均纯收入的时间序列模型

本文利用湖北省1980-2008年农村居民人均纯收入时间序列数据,建立了ARMA(自回归移动平均)模型进行时间序列分析.分析结果表明,ARMA(1,1)模型能够提供较好的预测结果,因而可以用其进行预测,为相关部门提供参考数据.     

广西GDP的时间序列分析与预测模型

文章利用时间序列分析中的ARIMA探索宏观经济预警系统中的基础数学模型。首先把广西1978～2008年GDP时间序列平稳化,ADF检验后确认二阶差分为平稳序列,根据ACF和PACF图并且结合AIC准则最终模型确定为ARIMA（2,0,3）。     

剔除通胀因素后中国人均消费支出的实证分析

根据一般消费理论,收入和价格是决定消费两个主要因素。根据1980-2006年我国消费样本数据建立了我国消费模型,通过EVIEWS软件利用OLS方法进行参数估计,并对模型进行了检验。经过计量分析得知我国人均消费水平受GDP影响,且人均消费水平与人均CGDP呈明显线性关系。若我国人均GDP增长1%,则人均居民消费水平约增加0.71%。滞后的人均消费水平对我国当年的人均消费水平的影响是不显著的。     

基于EKC的杭州市经济增长与环境质量演进关系研究

以EKC为理论基础,选取1983-2010年杭州市经济和环境数据,通过二次、三次函数模型拟合,建立最优模型,以此分析杭州市经济增长与环境质量演进的关系。结果表明:人均GDP与6种环境指标的EKC均呈现出倒U形的特征。其中工业废气排放量、人均工业废气排放量、工业废水排放量、人均工业废水排放量已越过转折点,出现在EKC右侧;工业固体废物产生量、人均工业固体废物产生量还处于EKC左侧。据此提出相应的政策建议。     

What has caused China’s economic growth?

Economic growth is driven by numerous factors. However, traditional economic theory focuses on certain key reasons, while ignoring the impact of other factors. Since 1978, China has achieved unprecedented economic growth, but also faces low per capita GDP. To clarify the driving forces behind this situation, we used per capita GDP to represent China’s economic growth and performed total factor analysis based on 13 variables in 7 socioeconomic dimensions using panel data from 30 Chinese provinces over the 40 years since China opened to the west in 1978. We found similar determinants in different regressions. Internal trade, privatization and investment were the primary factors driving Chinese economic development. Surprisingly, we found that the contribution of foreign trade to economic growth (per capita GDP) was weak. Education had a much smaller contribution than science and technology. Using per capita income as the dependent variable to provide a robustness test, we found that China’s income distribution has not paralleled its economic development and the distribution of the benefits of GDP growth to citizens must be improved. China’s experience demonstrates that promoting economic growth requires coordinated development of many factors, and that different policy preferences should be adopted to meet different economic development conditions.     

Demographic transition and economic growth in China,India and Pakistan

The authors of this paper adopt a Solow–Swan model extended to include demographic variables to analyze the overall effect of demographic transition on economic growth. The results, based on data from seventy countries over the period 1961–2003, reveal that GDP per capita growth is positively related to the growth differential between the working-age population and the total population, and negatively related to child and old-age dependency ratios. Based on these results, they find that population dynamics explain 46 percent of economic growth in per capita GDP in China over the period 1961–2003, 39 percent in India, and 25 percent in Pakistan. Furthermore, population dynamics are expected to have a positive effect on economic growth in India and Pakistan over the period 2005–2050, and a negative effect in China.     

福建省地级市经济发展水平综合评价

文章采用人均GDP、人均第三产业总产值、人均地方财政收入、进出口总额、城镇人口占总人口的比重等9个指标,运用主成分分析方法对福建省9个地级市的经济发展水平进行综合评价,并对其进行了聚类分析,进行分类比较,提出了相应的发展对策。     

On the simultaneity problem in the aid and growth debate

This paper shows that foreign aid has a significant positive average effect on real per capita gross domestic product (GDP) growth if, and only if, the quantitatively large negative reverse causal effect of per capita GDP growth on foreign aid is adjusted for in the growth regression. Instrumental variables estimates show that a 1 percentage point increase in GDP per capita growth decreased foreign aid by over 4%. Adjusting for this quantitatively large, negative reverse causal effect of economic growth on foreign aid shows that a 1% increase in foreign aid increased real per capita GDP growth by around 0.1 percentage points. Copyright © 2011 John Wiley & Sons, Ltd.     

The impact of the economic cycle on fatal injuries. The case of UK 1971–2007

The aim of this paper is to investigate the effect of the economic cycle on workplace accidents. In particular, the effect of the usual factors of the economic cycle (GDP per capita, Unemployment) is examined along with the effect of working hours (to account for flexible employment) on fatal injuries (to exclude the effect of under-reporting data) for the period 1971?C2007 in UK. Detailed multiple regression analysis is applied, which indicates a controversial and inelastic relation of GDP per capita (negative) and unemployment rate (positive), but also an elastic relation of working hours (positive) to fatal injuries. Further research in data of various countries is proposed before arriving to certain conclusions.     

Estimating the economic costs of organized crime by synthetic control methods

The economic costs of organized crime have been estimated for the case of southern Italy by Pinotti (Economic Journal 2015; 125, F203–F232, 2015): using synthetic control methods, he finds that, due to the advent of the Italian Mafia in the regions Apulia and Basilicata, GDP per capita dropped by 16%. Replicating this study in a narrow sense by estimating the same model with the same data, but using different software implementations, we observe minor differences stemming from the different implementations. By identifying the correct implementation, we find that the loss in GDP per capita due to the presence of the Mafia has been slightly overestimated.