Analysis of the impact of excess mortgages on housing prices using the cointegration test

This article attempts to explain and predict housing prices by constructing a model based on the variables that most influence demand: the theoretical purchase effort index without tax deductions as well as a new and innovative indicator that includes the excess of mortgages granted. The Johansen methodology for cointegration analysis reveals the existence of long-run equilibrium and the model’s subsequent ECM, to verify the statistical significance of the variables, confirms the validity of the model concerning this Spanish case study.     

Impact of oil price changes on Turkey’s exports

Substantial decline in oil prices observed since the second half of 2014 has brought forward discussions on the impact of oil prices on the external balance. This decline is expected to shift real income from oil exporter countries to oil importer countries. In this context, we study the effect of change in oil prices on Turkey’s exports taking into account the fact that Turkey’s export to oil exporting countries has approximately one-third share in total exports, while export to oil importing countries has a share of two-thirds. At the first step, we analyse the effect of oil prices on economic growth of trade partners of Turkey, where countries are grouped according to their net oil export position. We find that the effect of oil prices on different country groups’ growth is asymmetric. In the second stage, for two groups of countries, we estimate growth-export elasticity through Turkey’s export demand function. Finally, we calculate the net effect of oil prices on exports considering different income effects caused by oil price change on each country groups. Results indicate that the net effect of oil prices on the exports is limited given the current export shares.     

Deleveraging in a Highly Indebted Property Market: Who does it and are there Implications for Household Consumption?

A distinguishing feature of the period preceding the 2007/2008 financial crisis was the sizeable increase in private sector debt observed across many countries. A key component of household liabilities is mortgage debt and with many countries experiencing persistent increases in house prices from the mid‐1990s, a marked increase in this aspect of household leverage was observed. While aggregate statistics across countries confirm reductions in personal debt levels in recent years, relatively few sources of micro data are available to examine the nature of the deleveraging process at the household level. In this paper, using a unique dataset, we examine deleveraging amongst a representative sample of mortgaged Irish households. We identify the characteristics of households engaged in deleveraging and find that it is those households who can afford to deleverage who do. Furthermore we find some tentative evidence to suggest that the decision to deleverage has negative implications for household consumption.     

Oil price and Gulf Corporation Council stock indices: New evidence from time-varying copula models

Using a time-varying GJR copula approach, we determine the conditional dependence of the GCC stock indices on oil price between 2007 and 2016. We show how to improve the forecasting accuracy of the co-movement of energy and stock prices in an equally weighted portfolio. Contrary to prior findings, we demonstrate that due to the different co-movements across the GCC stock indices, portfolios of oil assets and several GCC stocks are less likely to be affected by systemic risk. The different co-movements across several stock indices over time provide different entry and exit points for stock investors. This approach is in line with the ‘buy low/sell high’ adage.     

中国粮食价格波动的成因及经济效应分析

选取1978—2011年的年度数据,运用协整对中国粮价波动的成因进行实证。结果表明：粮食生产量、农业生产资料价格指数、居民消费价格指数、粮食消费量、国际粮食价格、广义货币量和粮食库存量对粮食生产价格影响显著;粮食生产量、居民消费价格指数、粮食净进口量对粮食零售价格影响显著。而粮价波动的经济效应：2种粮食价格对粮食产量的影响不同;粮价上涨农民得到的很少;不能确定物价与2种粮食价格是否有关。最后提出了相关政策建议。     

Co‐movements in commodity prices: a note based on network analysis

This article analyses co‐movements in a wide group of commodity prices during the time period 1992–2010. Our methodological approach is based on the correlation matrix and the networks inside. Through this approach we are able to summarize global interaction and interdependence, capturing the existing heterogeneity in the degrees of synchronization between commodity prices. Our results produce two main findings: (a) we do not observe a persistent increase in the degree of co‐movement of the commodity prices in our time sample, however from mid‐2008 to the end of 2009 co‐movements almost doubled when compared with the average correlation; (b) we observe three groups of commodities which have exhibited similar price dynamics (metals, oil and grains, and oilseeds) and which have increased their degree of co‐movement during the sampled period.     

非洲猪瘟疫情对我国肉类价格影响的区域异质性研究

[目的]非洲猪瘟疫情暴发导致猪肉等畜产品市场供需结构性、区域性失衡,进而导致肉类价格大幅波动,不利于畜牧业高质量可持续发展。[方法]文章通过构建覆盖全国30个省（市、区,不含港澳台、西藏）,包括猪牛羊和白条鸡四大肉类价格和非洲猪瘟疫情指数的动态面板数据,运用面板向量自回归模型（PVAR）,研究非洲猪瘟疫情对猪肉等主要肉类价格的冲击和影响在重点、约束、适度发展区和潜力增长区(1)的区域异质性。[结果]（1）非洲猪瘟疫情对不同区域不同肉类价格的影响存在着正负向不趋同的方向性差异,在冲击程度大小和时滞期上均存区域异质性;（2）区域间和区域内不同省份间猪肉等肉类生产流通和供需形势、及非洲猪瘟发生发展程度的差异是非洲猪瘟疫情对这些肉类价格冲击影响异质性产生的主要原因。[结论]非洲猪瘟疫情对肉类价格影响存在较为明显的区域异质性,亟需进一步优化生猪等畜牧产业布局,加快形成区域协同发展格局;健全动物疫病防控体系,建立多方协同联动机制;完善市场风险预警调控机制,加快实现产需顺畅匹配,确保畜产品市场总体平稳运行和畜牧业健康可持续发展。     

北京市房地产价格影响因素分析及限购政策绩效评估

随着经济的高速发展,城市的房价也呈现出急剧攀升的态势,脱离了正常的价格波动轨道,大大增加了城市居民的生活成本。以首都北京为例,房价的上升幅度远远超过预期。在经济理论的基础上,运用近几年北京房地产行业的统计数据建立回归模型,可以对影响北京房价的因素进行分析,并且可以对北京市政府2011年2月出台的＂京八条＂限购政策进行绩效评估。     

Forecasting UK house prices: A time varying coefficient approach

Previous studies of UK house prices, developed from the demand and supply ofhousing or from the asset market approach have been poor in terms of robustness and ex-post forecasting ability. The UK housing market has suffered a number of structural changes, particularly since the early 1980s with substantial house price increases, financial market deregulation and the removal of mortgage market constraints through competition. Consequently, models which assume that the underlying data-generating process is stable and apply constant parameter techniques tend to suffer in terms of parameter instability. This article uses the Time Varying Coefficient (TVC) methodology where the underlying data-generating process in the UK housing market is treated as unstable. The estimation results of the TVC regression of UK house prices is compared with those obtained from three alternative constant parameter regressions. Comparisons of forecasting performance suggest the TVC regression out-performs forecasts from an Error Correction Mechanism (ECM), Vector Autoregressive (VAR) and an Autoregressive Time Series regression.