Revisiting the Exchange Rate Pass‐Through to Inflation in Africa’s Two Largest Economies: Nigeria and South Africa

This paper revisits the exchange rate pass‐through (ERPT) to inflation in Nigeria and South Africa by incorporating structural breaks and using time series variables, namely the consumer price index, nominal effective exchange rate, gross domestic product, and crude oil price. Based on the Maki cointegration test and a flexible estimation approach of the Autoregressive Distributed Lag (ARDL) model, our empirical evidence suggests that the long‐ and short‐run ERPT to inflation is complete for Nigeria, while for South Africa it is incomplete both in the long run and short run. This result indicates that prices are stickier in South Africa compared to Nigeria. The comparison between Nigeria and South Africa confirms the role of inflation targeting and central bank credibility on the ERPT. The results divulge further that output growth in Nigeria increases inflation in the long run while it is anti‐inflationary in the short run. For South Africa, the effect of output growth is negatively insignificant. In addition, the long‐run effect of oil price is negative and significant for Nigeria, while for South Africa the short‐run effect of oil price is positive and significant. Therefore, the findings of this paper will assist the monetary authorities to achieve monetary policy objectives.     

基于ACO优化的ARIMA-ES-RF布伦特原油价格预测研究

为解决传统单一的自回归积分滑动平均(ARIMA)和指数平滑(ES)预测原油价格(以布伦特原油为例)误差较大,难以精确地预测序列非线性特征的问题,提出自回归积分滑动平均(ARIMA)-指数平滑(ES)-随机森林(RF)组合预测方法。目前虽已有大量的原油价格预测模型,但还未有文献利用随机森林组合传统时间序列模型对原油价格进行研究。在此基础上,利用蚁群算法(ACO)对随机森林的重要参数(树的数量及根的深度)进行智能搜索,将随机森林组合模型的预测精度反馈给蚁群进行信息素的实时更新,输出使得组合模型预测精度最高的模型参数。研究结果表明：提出的蚁群优化参数后的组合随机森林模型能更好地预测布伦特原油价格的趋势,预测精度均方根误差(RMSE)从1.15降低至0.88,减少了0.27;平均相对误差从1.10%降低至0.86%,降低了0.24%,预测精度较以往的原油价格预测模型有显著提升。     

径向基函数网络的改进算法在油价预测中的应用

本文将径向基函数网络应用在国际原油价格预测中,采用一种改进的HCM算法来确定径向基函数的中心,并以纽约市场国际原油期货的日收盘价为对象进行预测,其结果表明,该模型具有较好的学习和泛化能力,为国际原油价格的预测提供了一条新的途径。     

A recession‐and‐state forecasting model

The state forecasting model (SFM) developed herein predicts the probability that a recession will begin or end within the next quarter. It is also important to forecast the state, as models prone to false alarms are not useful. The model combines parsimony, predictive accuracy, and ease of estimation using readily available data. No regressor is benchmark‐revised, and only one is seasonally adjusted. The SFM correctly forecasts, out‐of‐sample, the binary state in 163 of 164 quarters for an overall proportion of correct forecasts of 0.994. The results demonstrate the discriminating ability, longevity and striking forecasting ability of the model. A benchmark model based on the newly revised Leading Economic Index of the Conference Board has zero marginal predictive power in the presence the SFM.     

House prices in the Ottoman Empire: evidence from eighteenth‐century Edirne†

This study uses a new dataset of 2,246 notarial deeds of house sales from one of the major cities of the Ottoman Empire, Edirne, covering the period from 1720 to 1814. It estimates real hedonic house prices and urban wealth inequality for the housing market. It shows that house size, proximity to the commercial centre, access to fresh water, and family ties were important determinants of relative house prices. These findings also apply to the different quartiles of the market, indicating limited market segmentation. It demonstrates that there was an increase in housing wealth inequality during the eighteenth century as house prices became more dispersed. The hedonic house price index provides evidence that inflation‐adjusted house prices declined substantially following the Russo‐Turkish war of 1768–74. The decline is mainly explained through demographic shocks induced by plague epidemics, natural disasters, and other population movements driven by wars, army mobilization, and political upheavals.     

房地产市场价格的内生变动特征分析：以住房市场为例

本文从住房资产的消费和投资的二重性出发，分析了住房资产市场内在特征，进而揭示了住房市场价格的内生波动特征。本文的结论是：尽管根据一般衡理论，实现住房市场（或更一般地讲整个房地产市场）竞争性的市场均衡价格意味着效率最大，但是，由住房资产及其市场的内生特征破坏了住房价格趋向均衡的过程，因此住房市场价格的内生波动必然偏离均衡状态。这个结论也很容易推演至整个房地产市场。这一结论的政策含义是：在监测住房市场价格波动时，必须在充分考虑住房市场内在特征的基础上，以一般均衡理论为参照系，寻找能够逐渐接近住房市场一般价格均衡的条件和途径，而不是试图实现住房市场的价格均衡。     

Price‐Setting Behavior of Korean Firms†

This paper investigates a pattern of price revision by firms in Korea and sheds light on the cause of price stickiness by providing reliable statistical estimates for calibration of the parameters of the widely‐used macro‐models. Based on firm‐level survey data and using a probit model, we identify the firm characteristics or market conditions that discourage firms from carrying out state‐dependent price adjustment. We also estimate the factors driving firms to engage in state‐dependent adjustment rather than wait until the next scheduled revision under three different shocks: demand, general cost and exchange rate shocks. We find a few interesting features, as follows. First, price revision by Korean firms tends to be time‐dependent rather than state‐dependent, with a sizable dispersion across sectors and firm sizes. Second, the pattern of price revision in Korea is not significantly different from that in selected advanced economies. Third, the reason why firms favor time‐dependent price adjustments appears to be endogenous, accounted for by a number of market institution variables. Fourth, in response to shocks, Korean firms tend to wait until the next periodically scheduled revision rather than make a state‐dependent price adjustment, unless marginal costs are affected significantly by the shock, and state‐dependent revisions are often significantly delayed when they do occur.     

Economic Liberalization and Conditional Volatility of Exchange Rate in Sub‐Saharan Africa: Asymmetric GARCH Analysis

Abstract: For small open economies, an understanding of movements in the exchange rate is imperative in analyzing trade and capital flows. In addition, reliable forecasting of exchange rate volatility is important in risk‐taking assessment and investment decision‐making, both of which are critical to long‐term growth. Using an asymmetric GARCH‐type approach, this paper examines the implications of economic liberalization on the stochastic behavior of the exchange rate series in a sample of sub‐Sahara African (SSA) countries over the 1970–2004 period. The results indicate that exchange rate volatility is variable, and is less volatile under fixed exchange rate regime (pre‐economic liberalization) and higher under flexible regime (post‐economic liberalization), that is, it is asymmetric. For most of the countries, the EGARCH and TGARCH models are robust to parameter stability and gives better forecasting performance compared to the standard GARCH model.     

Housing Markets in China and Policy Implications： Comovement or Ripple Effect

The overheated housing market has recently become a top priority of the Chinese authorities and whether the ripple effect exists is key to understanding this housing issue. The present paper uses a cointegration estimation technique for six first-tier Chinese cities during the 2003-2013 period to show that the comovements among housing prices in China are fully reflected in a long-run equilibrium. Using the Toda- Yamamoto causality test, the ripple effect is found to be characterized by a lead -lag relationship. More importantly, it is found that Beo＇ing is the main source of housing price appreciation in China, and should be targeted as the regulatory object to efficiently resolve the troubles in this increasingly high housing-price era.     

Portfolio modelling and growth in open economies

The standard BRANSON model is modified in a way which allows one to focus on the short term dynamics of foreign bonds markets, the money market and the stock market—or alternatively the oil market. This allows us to explain the dynamics of the exchange rate and the oil price within a portfolio choice model; also we identify critical expectation dynamics in a more conventional pricing approach to the oil market—expectations determine whether or not the oil market equilibrium is compatible with a stationary price or with sustained oil price inflation. Moreover, a straightforward innovative way to combine a portfolio approach with a growth model is developed. New results are obtained—through multiplier analysis—about the long term effects of changes in the savings rate, the process innovation rate, the product innovation variable and the money supply on the exchange rate and the stock market price; this raises many empirical issues. Finally, the analysis presented sheds new light on the global asset price dynamics in the context of the banking crisis. To the memory of Edward Graham, Petersen Institute for International Economics, Washington D.C.     

THE PREDICTABILITY OF STOCK MARKET RETURNS IN SOUTH AFRICA: PARAMETRIC VS. NON‐PARAMETRIC METHODS

This paper compares the forecasting performance of a sub‐class of univariate parametric and non‐parametric models in predicting stock market returns in South Africa. To account for conditional heteroskedasticity in stock returns data, the non‐parametric model is generated by the conditional heteroskedastic non‐linear autoregressive (NAR) model, while the parametric model is produced by the generalised autoregressive conditional heteroskedastic in mean (GARCH‐M) model. The results of the paper show that the NAR as a non‐parametric model performs better than the GARCH‐M model in short‐term forecasting horizon, and this indicates the importance of a distribution‐free model in predicting stock returns in South Africa.     

The impact of world oil price shocks on macroeconomic variables in Vietnam: the transmission through domestic oil price

This study examines the impact of world oil price shocks on macroeconomic variables in Vietnam with a focus on the transmission channel of domestic oil prices. The Structural Vector Autoregression model with two blocks of real economy variables and monetary variables is employed. The world oil price follows an autoregressive process to reflect the exogenous nature of world oil price shocks to the domestic economy. The retail domestic oil price is determined simultaneously by only the world oil price due to the government's control of the domestic oil market. Using monthly data in the period between 2009 and 2021, the study indicates that a positive shock to world oil prices will increase the domestic oil prices significantly, industrial production (slightly and only statistically significant in the third month after), and inflation (significantly in 8 months). Besides, the domestic oil price is not the only transmission channel of world oil price shocks to the economy. This result implies forecasting, assessing, and controlling the impact of the world oil price shock on the economy should focus on both domestic oil prices and other indirect channels.     

Housing Prices, Mortgage Payments and Savings Behavior in Taiwan: A Time Series Analysis

After reaching its peak at the year of 1987, the saving rate of Taiwan dropped quickly in the late 1980s. At the same time, the real average housing prices in Taiwan had increased almost three times from 1987 to 1990. Why did the savings rate in Taiwan drop so quickly after 1987? Does it relate to the dramatic increase in housing prices? Although it has been confirmed that there is a negative wealth effect of housing price appreciation on savings, the estimated wealth effect on savings could be biased if the effect of mortgage payment (also known as forced savings) on saving is neglected. Applying quarterly data from 1981 to 2000 in Taiwan, we employ a time series analysis to compare two saving models, the traditional one and the one with forced saving. As we expected, the negative wealth effect of housing price appreciation on saving is smaller in the forced saving model than in the traditional saving model. By the estimated error correction models (ECMs), ignoring the impact of housing price appreciation on forced saving, the speed of short‐run adjustment in total saving would be significantly slower. For forecasting purposes, the forecast errors in ECM of the forced saving model are smaller than that in the total savings model.     

Pricing Natural Gas in Mexico: An Application of the Little‐Mirrlees Rule—The Case of Quasi‐Rents

In 1997, the Comisión Reguladora de Energía of Mexico implemented a netback rule for linking the Mexican natural gas price to the Texas price. At that time, the Texas price reflected a reasonably competitive market. There have been dramatic increases in the demand for gas, and there are various bottlenecks in the supply of gas. As a result, the price of gas in Texas now reflects the quasi‐rents created by these bottlenecks. We show that it is optimal for the Mexican government to use the netback rule based on the Texas price of gas to set the price of gas in Mexico even though the Texas market cannot be considered a competitive market, and the Texas price for gas reflects quasi‐rents created by various bottlenecks.     

基于神经网络模型的智能产业板块股价探究

针对金融波动性和市场风险,基于A股市场上70余只智能板块的股票近10年的四因子数据,从神经网络模型入手实证分析,利用随机梯度算法对收盘价预测,比较预测值与实际值的模型误差及损失函数,进行因子选取、算法改进及指标择优。结果表明,神经网络模型参数在批次为2、迭代次数为4 150时,MSE(均方误差)、MAPE(平均绝对百分比误差)、MAE(平均绝对误差)分别为60.191 1、30.732 6、4.803 2,收盘价的拟合效果最佳,该参数下的神经网络模型可用于探究股票市场价格趋势,为投资者、金融机构提供一定参考依据。     

基于灰色关联度的安徽省房价影响因素的分析

以安徽省2001-2010年房地产相关资料为依据,适当选取房价影响因素指标,引入灰色关联分析方法,构建房价影响因素的灰色关联度模型,定量地计算出各指标与房价的灰色关联度。结果表明:人口总数、居民消费价格指数、税收三大因素对房价影响最大,而住宅施工面积、住宅销售额、住宅投资完成额影响较小。     

Examining the impact of home purchase restrictions on China's housing market

This paper studies the impact of home purchase restrictions on China's housing market. We estimate a structural model of household preference for housing, real estate developers' pricing decisions, and equilibrium market outcome in five large cities. By comparing the estimation results from pre- and post-policy intervention, we find that, after home purchase restrictions are implemented, overall housing demand in most cities becomes weaker and less price elastic; meanwhile, real estate developers face higher holding costs and thus are willing to lower prices and sell more quickly. Counterfactual analyses show that in some cities alternative policy designs that cause less structural change of demand could achieve larger consumer welfare and social welfare than the implemented policy.     

基于优化BP网络的电网短期负荷预测研究

如何提升电网负荷短期预测水平是电网企业亟待解决的问题。本文针对传统的BP神经网络算法所存在的学习过程收敛速度慢、算法易陷入局部极小点和鲁棒性差等缺陷,引入粒子群优化算法对其进行优化和改进,使之具备更加完善的性能。通过实际电网负荷预测的实验与比较,证明了所构建的符合预测系统的准确度。     

基于GARCH族模型的上海市住宅市场价格波动的特征研究

住房问题是关系国计民生的重要问题,研究住宅市场的价格波动规律对消费者购买时机选择、调控政策的制定等具有重要的参考价值。鉴于此,以住宅市场收益率的变化来衡量住宅市场价格的波动,采用2006-2016年上海市新建住宅和二手房月度收益率时间序列作为样本,通过构建GARCH族模型对上海市新建住宅和二手房市场的价格波动特征进行研究。研究表明：上海市新建住宅市场的价格波动存在显著的自相关现象,但不存在显著的集聚性、非对称性以及高风险高回报的特征;二手房市场的价格波动存在显著的自相关现象,具有显著的集聚性,即二手房市场本期或过去若干期的波动较大时,未来几期的波动也会很大,反之亦然;二手房市场价格的波动不存在显著的非对称性及高风险高回报的特征。