基于小波分析和最小二乘法的能源消费预测

能源是人类赖以生存的物质基础,有效地预测能源工程对于经济的发展和社会的进步具有重要意义。小波分析在时域和频域上都有表征信号局部信息的能力,能够去除数据中的非正常成分,平滑奇异数据。本文通过与最小二乘法的比较与结合,选用d3小波,先利用小波分解与重构对能源消费总量进行预处理,再使用最小二乘法进行拟合和预测,事实证明,比单纯最小二乘法的拟合效果更好,具有推广意义。     

百分位数回归及应用研究

在进行定量分析时,最小二乘法已经成为一种可信赖的工具。但是运用最小二乘法的条件比较高,在实际问题中,完全满足条件的情况并不多见,那么在应用时就难以得到无偏的、有效的参数估计量。针对上述问题,以OILPLUS公司取暖用燃油消耗的分布为主要研究对象,在进行参数估计时,应用百分位数回归方法,既可以看到采用百分位数回归方法与采用最小二乘法得到的模型显著不同,又可以得到比最小二乘法更为丰富的信息。     

基于偏最小二乘回归分析法的汽车4S店客户满意度研究

客户满意度（CSI）始终是汽车销售企业最为关注的管理指标之一。采用偏最小二乘法回归分析的方法,可以就目前顾客满意度多项指标建立数学分析模型,从而建立良好的顾客满意度指数测评体系。通过该测评体系,汽车4S店可以回归分析和计算相关因数,得到顾客满意度相关指标的提升建议,进而优化和改进相关服务。     

基于最小二乘法分析第三产业对国民总收入的影响

最小二乘法是经济分析中应用最普遍的方法之一,我们应用最小二乘法分析第三产业发展对国民总收入的影响,结果表明,国民总收入是第三产业的线性函数关系。我们选取1978--2010年中国GDP和第三产业收入数据作为样本数据,建立模型分析中国GDP与第三产业收入的关系。     

我国社会科学研究投入产出绩效研究

把反映社会科学领域水平较高的论文作为科研产出指标,采用偏最小二乘回归(PLS)方法对我国社会科学研究投入与产出进行建模分析,揭示了影响我国社会科学产出的主要投入要素,采用投入产出比分析了各地高校、科研机构以及各学科的研究效率。     

基于两种组合模型的安康市卷烟预测思想与运用研究

卷烟市场预测行为由于受到众多相关因子的影响,成为目前营销工作的一个难题。文章以2005-2009年的安康市卷烟销售数据统计分析为依据,将最小二乘法、指数平滑法、ARIMA预测模式相结合,对全市卷烟进行了年度预测和月度预测,尤其是对高档卷烟的消费需求变化进行了分析,在实践中有较强的实用意义。     

承保保险金额的预测与分析

保险总准备金是巨大火灾损失发生的年分之前，按照一定的比例从保险费收入中逐年提留适度的金额，积累起来作为发生巨灾时的赔付基金。而历年的保险费是按一定的费率以承保额为基础来计算和收取。这说明，为了进行保险总准备金的度规模讨论，需要对历年承保的保险金额进行预测与分析，预测历年承保金额的方法较多，这里主要介绍如何用最小二乘法进行承保额的预测与分析。     

以曲线拟合预测我国经济发展和工资增长

将在中国统计年鉴中收集到的1978-2009年全国GDP、GNP的相关数据转化为曲线,通过对比曲线趋势图,简单、合理的假设了未来我国经济发展和工资增长的趋势。并以山东省为例,用最小二乘法在EViews软件中拟合出1978年-2010年职工年平均工资的增长曲线方程,也根据得出的等式合理预测了2011年-2035年山东省职工年平均工资,以印证前面的预测。     

大学城科技园区的经济集聚效应--基于预期模型的实证分析

随着中国高等教育的不断普及,关于大学城的建设问题已经引起了很多学者的关注。同时大学城兴起的同时所带来的周边产业的不断集聚现象也有不少人正在研究单,但一直都缺少实证分析。因此本文以蚌埠大学城科技园区为研究对象,以最小二乘法和层次分析法为主要的分析方法,利用预期模型对蚌埠大学城科技园区经济集聚效应做出定性与定量相结合的实证分析。基于实证分析我们可以得出大学城科技园区的经济集聚效应并对科技园区的建设提出意见。     

安徽城镇居民消费与收入之间关系的计量分析

以《安徽统计年鉴》1990—2003年期间的部分统计数字作为样本值，用最小二乘估计方法估计出城镇居民个人消费函数不带时间标志的静态计量经济模型以及用阿尔蒙估计法估计出的带有时间序列的跨时期动态计量经济模型。分析影响安徽省城镇居民消费支出的有关因素及存在问题，希望对安徽省城镇居民个人消费进行宏观预测和调控时提供计量上的参考。     

Returns to schooling in Kazakhstan

This paper examines rates of return to schooling in Kazakhstan using OLS (Ordinary Least Squares) and instrumental variable (IV) methodologies. We use spouse's education and smoking as instruments. We find that spouse's education is a valid instrument and that conventional OLS estimates that assume the exogenous nature of schooling, and hence do not control for endogeneity bias, may underestimate the true rates of return. The results indicate that the returns to schooling in Kazakhstan have increased with transition. This may reflect the relative scarcities of highly educated people in Kazakhstan with human capital that employers require and, following the market reforms, reward accordingly.     

Socio-economic and environmental factors in the global spread of COVID-19 outbreak

COVID-19 is a virus with a very fast spread rate in the world. Therefore, knowledge of factors that may explain such spread is paramount. The main objective of this research was to analyze the determinants of the virus spread worldwide. Unlike previous studies that were limited to traditional factors, this research extends the analysis to government measures (quarantine, containment, and response budget) against the spread of the virus. Thus, an econometric model relating the variable of interest to a number of variables was carried out using the Ordinary Least Squares (OLS) and the Two Steps Least Squares (2SLS) methods on a sample of 163 countries. The main findings indicate that economic factors such as the level of development, the degree of trade openness and the response budget to the COVID-19 pandemic, have a positive effect on the spread of the virus. With regard to social factors, the population density and confinement are major causes of the spread of the virus. Finally, temperature contributes to reduce the spread of the virus. These findings are robust to the estimation technique and to the measurement of the spread of the virus considered. In the light to these findings, implications for economic policies have been drawn.     

Does access to credit improve productivity? Evidence from Bulgaria1

Although it is widely accepted that financial development is associated with higher growth, the evidence on the channels through which credit affects growth at the microeconomic level is scant. Using data from a cross‐section of Bulgarian firms, we estimate the impact of access to credit, as proxied by indicators of whether firms have access to a credit line or overdraft facility, on productivity. To overcome potential omitted variable bias of Ordinary Least Squares (OLS) estimates, we use information on firms’ past growth to instrument for access to credit. We find credit to be positively and strongly associated with TFP. These results are robust to a wide range of robustness checks.     

The dynamics of inflation: a study of a large number of countries

Over the last twenty years the statistical properties of inflation persistence has been the subject of intense investigation and debate without reaching a unanimous conclusion yet. In this article we attempt to shed further light to this debate using a battery of econometric techniques in order to provide robust evidence on the degree of inflation persistence and whether this has changed during the period in which several countries have followed inflation-targeting regimes or new monetary regimes. We consider the inflation rates of thirty developed and emerging economies using quarterly data for the period 1958 to 2007 which include alternative monetary policy regimes. The coefficient of the inflation parameter is estimated by Ordinary Least Squares (OLS), Autoregressive Moving Average (ARMA) and Autoregressive Fractionally Integrated Moving Average (ARFIMA) models. Furthermore, the grid-bootstrap Median Unbiased (MUB) estimator approach developed by Hansen (1999) is used to estimate the finite sample OLS estimates coupled with the 95% symmetric confidence interval. We also examine parameter stability of persistence coefficients by estimating a model with time-varying parameters.     

Tobit or OLS? An empirical evaluation under different diary window lengths

Researchers analysing time-use data often estimate limited dependent variable models because time spent must be nonnegative and cannot be more than the total amount of time in a given observation period. While the traditional empirical technique applied to such cases is maximum likelihood estimation of a Tobit (censored regression) model, recent debate has questioned whether linear models estimated via Ordinary Least Squares (OLS) are preferable. On the one hand, Tobit models are deemed necessary to address the significant censoring (i.e. large numbers of zeroes) typically found in time-use data, in the face of which OLS estimators would be biased and inconsistent. Yet, optimization occurs over a longer period than that covered by the typical time diary (often a day), and thus some argue that reported zeroes represent a measurement problem rather than true nonparticipation in the activity, in which case OLS would be preferred. We provide direct empirical evidence on this question using the Australian Time Use Surveys, which record time-use information for two consecutive diary days, by estimating censored and linear versions of a parental child care model for both 24-hour and 48-hour windows of observation in order to determine the empirical consequences of estimation technique and diary length.     

The gender pay gap in Russia during the transition, 1992-96

This paper explores the link between rising wage dispersion in Russia over the transitional period and the gender pay gap. The work of Blau and Kahn (1996) emphasized a role for 'wage structure' in the determination of the gender pay gap, although some interpretational issues concerning their methodology have been raised recently by Suen (1997). The unadjusted gender pay gap between 1992 and 1996 exhibited some degree of stability, but the analysis presented identified increased wage dispersion as a modest agent for the widening of the gap in Russia. Ordinary Least Squares (OLS) estimates for an equation pooling observations from both gender groups, registered no statistical difference in the mean ceteris paribus gender pay gap between the two years. To complement the mean regression approach, quantile regression procedures were also employed. Although the median regression provided evidence of a statistically significant temporal increase in the gender pay gap, this finding was not supported at other chosen quantiles of the wage distribution. This result was taken to highlight the possible sensitivity of the OLS procedure.
JEL classification: J16, J31, P23.     

Central Government versus private sector wages and cognitive skills: evidence using endogenous switching regression

The importance of estimation techniques that allow for nonrandom selection of workers into the public and private sectors has been established in the theoretical and empirical literature. A separate body of work has explored the contribution of cognitive and other basic skills to earnings. This article brings together these two strands of empirical literature using Adult Literacy and Lifeskills (ALL) survey data for Norway and Bermuda. In the case of Norway, results from both Ordinary Least Squares (OLS) and a switching regression model agree that cognitive skills are rewarded more in the public sector and that, in both sectors, the main effect is the direct effect of skills on earnings. In the case of Bermuda, however, switching regression estimates are substantially different with respect to the how skills affect earnings; furthermore, controlling for cognitive skills changes the nature of selection and, hence, the estimates of sector wage differentials.     

Forecasting China's inflation in a data-rich environment

Inflation is one of the most recent critical issues facing China. To improve inflation forecasts within China, this study investigates the predictive ability of three dimension reduction techniques used in a data-rich environment: Principal Components Analysis (PCA), Sliced Inverse Regression (SIR), and Partial Least Squares (PLS) applied in the Factor-Augmented Autoregression (FAAR) model proposed by Stock and Watson (2005). Varied macroeconomic data from China between January 1998 and December 2009 are obtained to construct factors for use by three different techniques. The performance of different dimension reduction methods depends on forecasting horizons, the number of factors chosen, and the number of slices for SIR. The empirical study finds that the FAAR model with an optimal number of PCA factors outperforms the other model in out-of-sample inflation forecasting in China.     

The J‐Curve: Evidence from Fiji*

This article provides new evidence on both long run and short‐run determinants of trade balance for Fiji and investigates evidence of J‐curve adjustment behaviour in the aftermath of a devaluation. We adopt a partial reduced form model that models the real trade balance directly as a function of the real exchange rate and real domestic and foreign incomes. Cointegration analysis is based on a recently developed autoregressive distributed lag approach—shown to provide robust results in finite samples. The long run elasticities are also estimated using a dynamic ordinary least squares approach and the Fully Modified Ordinary Least Squares (FM‐OLS) approach. Amongst our key results we find that there is a long‐run relationship between trade balance and its determinants. There is evidence of the J‐curve pattern; growth in domestic income affects Fiji’s trade balance adversely while foreign income improves it.     

Market power versus efficiency under uncertainty: conventional versus Islamic banking in the GCC

In this article we estimate the effect of concentration on intermediation margins in Gulf Cooperation Council's (GCC) Islamic and conventional banking under the assumption that margins are uncertain. The empirical model, which we formally derive from an expected utility maximization problem, allows us to test for risk aversion as well as competitive conduct in loan and the deposit markets. The model also yields an expression showing that the effect of concentration on margins is the sum of its respective effects on market power, marginal cost of intermediation and marginal cost of uncertainty. The expression allows us to test whether concentration is welfare enhancing, reducing or neutral. We find Islamic banks to be risk-averse and conventional banks to be risk-neutral. We also find that concentration is welfare-neutral in Islamic loans and deposits, welfare-enhancing in conventional loans and welfare-neutral in conventional deposits. We used Nonlinear Two-Stage Least Squares (N2SLS) and Nonlinear Three-Stage Least Squares (N3SLS) to check for robustness.