Speculative bubbles or market fundamentals? An investigation of US regional housing markets

This paper investigates the existence of speculative bubbles in the US national and 21 regional housing markets over three decades (1978–2015). A new method for real-time monitoring exuberance in housing markets is proposed. By taking changes in the macroeconomic conditions (such as interest rate, per-capita income, employment, and population growth) into consideration, the new method provides better control for housing market fundamentals and thereby it is expected to significantly reduce the chance of false positive identification. Compared with the method of Phillips et al. (2015a, 2015b), the new approach finds a dramatic reduction in the number of speculative housing markets and shorter bubble episodes in the US. It locates only one bubble episode in the early-to-mid 2000s over the whole sample period in the national housing market. At the regional level, it identifies two periods of speculation: late 1980s and early-to-mid 2000s. The early-to-mid 2000s bubble episode lasts longer and involves 16 metropolitan statistical areas.     

Forecasting using heterogeneous panels with cross-sectional dependence

In this paper, we focus on forecasting methods that use heterogeneous panels in the presence of cross-sectional dependence in terms of both spatial error dependence and common factors. We propose two main approaches to estimating the factor structure: a residuals-based approach, and an approach that uses a panel of auxiliary variables to extract the factors. Small sample properties of the proposed methods are investigated through Monte Carlo simulations and applied to predict house price inflation in OECD countries.     

Impact of macroeconomic surprises on the Brazilian yield curve and expected inflation

This study investigates how unexpected announcements in Brazilian and U.S. macroeconomic indicators affect the term structure of nominal interest rates, as well as implicit inflation expectations and real interest rates. Using daily data from March 2005 to December 2012, we employ an extended Vector Error Correction Model to take into account nonstationarity and the long-term equilibrium among different maturities of those curves. We found empirical evidence that macroeconomic surprises, domestic (Brazilian) and external (U.S. American), which lead the market to believe that there might be a higher risk of inflation or an overheated economy, raise nominal interest rates, implicit expected inflation and real interest rates. Surprisingly, in relation to the efficient-market hypothesis, we found that some macroeconomic surprises have a lagged effect on the yield curves. We also tested the impact of the global financial crisis of 2007–09 and found that the crisis affected significantly the direction and magnitude of the responses to macroeconomic news.     

The determinants of commercial banking profitability in low-, middle-, and high-income countries

Using a broad bank-level dataset and the GMM estimator technique described by Arellano and Bover (1995), this paper analyses how bank-specific characteristics, macroeconomic variables, and industry-specific factors affect the profitability of 10,165 commercial banks across 118 countries over the period from 1998 to 2012. Grouping the countries according to three income levels, we show that the determinants of bank profitability included in our model can explain existing profitability differences among commercial banks in low-, middle-, and high-income countries. The profitability determinants vary quite widely across the different levels of income in terms of significance, sign and size of the effect. The level of income has thus an important impact on the determinants of bank profitability.     

浅析宏观经济政策对金融市场的影响

近几年来,国内经济的发展可谓势头猛增,国家出台了一系列的宏观经济政策,这些宏观经济政策对我国金融市场的发展具有一定的影响。本文就国家的宏观经济政策对我国的金融市场产生的影响进行浅析评论。     

湖南宏观经济模型与经济波动

针对湖南经济波动的剧烈程度高于全国这一事实,建立一个湖南经济波动的预警模型.同时以政府消费和出口为先决变量,以GDP、居民消费和投资为内生变量,利用3SLS法建立一个联立方程组作为湖南的宏观经济模型.模型分析表明,政府消费对GDP等重要变量的乘数效应较大,因而应加大对政府消费的调控.在此基础上,结合ARMA模型和宏观经济波动模型对2010年以前的GDP、消费和投资增长率进行预测,通过系统化分析方法量化以上变量的无警区间,结果表明湖南未来几年的GDP、消费和投资波动将趋于稳定.     

收入分配、金融发展与宏观风险：一个文献综述

从收入分配角度解释金融危机是当前国际上正在热烈讨论的重要议题。本文旨在对这一研究领域的发展历程和最新进展做一个简单的综述。文章沿着收入分配研究的两条发展脉络——基于要素的收入分配理论和基于人际的收入分配理论——展开,并且分别考察了金融发展在两条路径的逻辑链条中起到的作用。最后,在回顾文献的基础上．提示出我国经济中潜在的宏观风险,得到对中国有借鉴意义的结论和启示。     

MACROECONOMIC UNCERTAINTY AND CONDITIONAL STOCK MARKET VOLATILITY IN SOUTH AFRICA*

This paper analyses how systematic risk emanating from the macroeconomy is transmitted into stock market volatility using augmented autoregressive Generalised Autoregressive Conditional Heteroscedastic (AR‐GARCH) and vector autoregression (VAR) models. Also examined is whether the relationship between the two is bidirectional. By imposing dummies for the 1997‐1998 Asian and the 2007‐2009 sub‐prime financial crises, the study further analyses whether financial crises affect the relationship between macroeconomic uncertainty and stock market volatility. The findings show that macroeconomic uncertainty significantly influences stock market volatility. Although volatilities in inflation, the gold price and the oil price seem to play a role, it is found that volatility in short‐term interest rates and exchange rates are the most important, suggesting that South African domestic financial markets are increasingly becoming interdependent. Finally, the results show that financial crises increase volatility in the stock market and in most macroeconomic variables, and, by so doing, strengthen the effects of changes in macroeconomic variables on the stock market.     

What caused the rise of Airbnb? An examination of key macroeconomic factors

The social and economic implications of the Airbnb phenomenon have been the subject of much research. Yet, the academic literature on Airbnb is nascent. Specifically, the issue of whether major macroeconomic conditions affect the supply of Airbnb has not been investigated. To address this gap, we propose a conceptual model that explains the determinants of Airbnb supply and examine the extent to which major macroeconomic factors affect the supply of Airbnb. Specifically, we analyze the effects of hotel room rates (ADR), hotel demand, tourism demand, house prices, gross domestic product (GDP), wages and unemployment on the supply of Airbnb in 50 U.S. states. Results show that increases in hotel ADR, house prices, and GDP have contributed to an increase in the supply of Airbnb, whereas increases in unemployment rates and wages have adverse effects on Airbnb supply. Theoretical and policy implications are discussed within realms of macroeconomic theory.     

Linking words in economic discourse: Implications for macroeconomic forecasts

This paper develops indicators of unstructured press information by exploiting word vector representations. A model is trained using a corpus covering 90 years of Wall Street Journal content. The information content of the indicators is assessed through business cycle forecast exercises. The vector representations can learn meaningful word associations that are exploited to construct indicators of uncertainty. In-sample and out-of-sample forecast exercises show that the indicators contain valuable information regarding future economic activity. The combination of indices associated with different subjective states (e.g., uncertainty, fear, pessimism) results in further gains in information content. The documented performance is unmatched by previous dictionary-based word counting techniques proposed in the literature.