Monetary policy and food inflation in South Africa: A quantile regression analysis

Although optimal monetary policy stabilizes food inflation theoretically, empirical studies remain limited not only in the context of volumes and the estimation approaches, but are focused on selected advanced and emerging countries to the neglect of Africa where poverty and dominance of food in the consumption basket are more pronounced. We provide empirical evidence in the context of South Africa using quantile regressions. Rising food prices are destabilized even further by restrictive monetary policy; a finding that has ramifications for inflation targeting, especially given that a quarter of the country’s population is food poor.     

COVID-19, stock market and sectoral contagion in US: a time-frequency analysis

We assess the conditional relationship in the time-frequency domain between the return on S&P 500 and confirmed cases and deaths by COVID-19 in Hubei, China, countries with record deaths and the world, for the period from January 29 to June 30, 2020. Methodologically, we follow Aguiar-Conraria et al. (2018), by using partial coherencies, phase-difference diagrams, and gains. We also perform a parametric test for Granger-causality in quantiles developed by Troster (2018). We find that short-term cycles of deaths in Italy in the first days of March, and soon afterwards, cycles of deaths in the world are able to lead out-of-phase US stock market. We find that low frequency cycles of the US market index in the first half of April are useful to anticipate in an anti-phasic way the cycles of deaths in the US. We also explore sectoral contagion, based on dissimilarities, Granger causality and partial coherencies between S&P sector indices. Our findings, such as the strategic role of the energy sector, which first reacted to the pandemic, or the evidence about predictability of the Telecom cycles, are useful to tell the history of the pass-through of this recent health crises across the sectors of the US economy.     

改革开放以来广州经济增长因素分析

本文从实证角度建立计量模型,利用主成分分析方法和最小二乘回归的方法,对广州改革开放30多年以来的经济增长因素进行了具体分析,研究表明改革开放30多年来,广州经济增长的促进因素主要是劳动力数量的增长,经济制度的变革,产业结构的升级,以及人力资本增长的作用,物质资本不是促进广州经济增长的主要因素。     

Use of minimum risk approach in the estimation of regression models with missing observations

This article considers a linear regression model with some missing observations on the response variable and presents two estimators of regression coefficients employing the approach of minimum risk estimation. Small disturbance asymptotic properties of these estimators along with the traditional unbiased estimator are analyzed and conditions, that are easy to check in practice, for the superiority of one estimator over the other are derived. Received May 2001     

中国外商直接投资的区位决定因素分析:城市数据

本文以全国210个地级以上城市为对象,分析了外商直接投资的区位决定因素。本文采用OLS和逐步回归分析方法以及2002年的横截面数据,在以往研究的基础上选择四项区位决定因素包括三种成本因素、三种市场因素、四种集聚因素和四种制度因素进行实证研究。结果表明,劳动力成本对各城市的外商直接投资的区位选择影响不明显,而市场规模、基础设施、教育和研究开发条件以及地方金融规模对外商直接投资的区位选择的影响具有显著性。本文的逐步回归分析结果还表明,就东部地区而言,能源条件和市场规模是较重要的区位决定因素;就中西部地区而言,市场规模、基础设施、教育和研究开发条件以及地方金融成为较重要的区位决定因素。     

Pseudo empirical likelihood method in the presence of missing data

In this paper, we propose an estimator for the population mean when some observations on the study and auxiliary variables are missing from the sample. The proposed estimator is valid for any unequal probability sampling design, and is based upon the pseudo empirical likelihood method. The proposed estimator is compared with other estimators in a simulation study.     

How do economic policy uncertainty and geopolitical risk drive Bitcoin volatility?

We investigate how economic policy uncertainty (EPU) and geopolitical risks (GPR) impact Bitcoin volatility with respect to factors related to type and nationality of uncertainty, investigated period, relationship horizon and extreme conditions. Applying ARDL model and quantile regression for monthly data from August 2010 to September 2021, we reveal that June 2014 corresponds to a key date that marks a reversal in the investigated relationship. Furthermore, we show that the relationship between uncertainty and bitcoin volatility changes according to different factors. US uncertainty has short run effects on Bitcoin volatility, while China’s uncertainty has rather long run effects. Moreover, Bitcoin volatility responds in the same manner to US EPU and GPR, while, it responds differently to China's EPU and GPR. In extreme quantiles, we find that Bitcoin hedges against US EPU and GPR. Further, Bitcoin hedges against either individual or joint effects of US uncertainty, but not both.     

商业银行盈利能力影响因素的实证分析——基于偏最小二乘回归（PLSR）算法

运用偏最小二乘回归模型及其辅助分析手段对商业银行盈利能力影响因素进行一次深入、细致、系统的梳理。研究表明,影响商业银行盈利能力的前六大因素依次为净息差、资产质量、成本收入比、风险承受能力、金融创新及存贷比,而银行资产规模对盈利能力的贡献度最低。为提升商业银行盈利能力,必须强化金融创新能力、防控商业银行风险、完善金融监管体制。     

回归分析法在经济预测中的应用浅析

回归分析法是在经济预测中常用的方法之一，它是在观察和分析经济发展的历史和现状的基础上，按照一定的方式建立反映其关系的数学模型，然后根据自变量在未来的变化来计算预测变量的变化，从而对未来的经济发展趋势进行预测。其关键是建立回归模型，并进行相关分析和结果预测。