Does the Reserve Bank of Australia follow a forward-looking nonlinear monetary policy rule?

ABSTRACT

The conventional monetary policy rule describes a simple linear relationship between the domestic interest rate, inflation rate and output gap. An important extension to this rule is to incorporate the forward-looking behaviour of central banks, where it is assumed that they target an expected level of inflation instead of its current realised value. Using quarterly observations for the period 1993:1-2018:2, this paper investigates whether the conduct of monetary policy in Australia can be described by a forward-looking linear monetary policy rule, or by a nonlinear forward-looking monetary policy rule. In particular, the nonlinear forward-looking monetary policy rule is analysed in a regime-switching framework using a smooth logistic transition regression model. While the results show that the conventional forward-looking linear monetary policy rule describes the application of monetary policy in Australia reasonably well, the interest rate setting behaviour of the RBA is best described by a nonlinear forward-looking monetary policy rule.     

The long breadth of cities: revisiting worldwide urbanization patterns, 1950–2030

ABSTRACT

A comparative analysis of population dynamics worldwide contributes to profile distinctive demographic and economic trajectories of urban growth, discriminating processes of settlement concentration or dispersion under sequential cycles of urbanization. However, a wide-ranging characterization of urban cycles based on demographic dynamics worldwide is still missing. The present work is aimed at filling such a gap analysing long-term changes (1950–2030) in annual population growth rate of 1691 urban agglomerations with more than 300,000 inhabitants in 74 world countries. Results of this study indicate that metropolitan growth worldwide was associated with largely variable rates of population growth, highly positive before 2000 and progressively reducing over recent decades. Despite important differences at continental (and country) scale, demographic expansion of urban agglomerations showed two contrasting phases with a break point in the 1980s denoting a progressive reduction in spatial heterogeneity of population growth rates and a moderate slowdown in demographic dynamics. Intensity of urban expansion and spatial heterogeneity in population growth rates across metropolitan agglomerations evidences a trade-off between fast and slow demographic dynamics. These findings can be better understood to support theories of sequential city growth, making a suitable contribution to policy making, especially in countries where urban population is expanding more rapidly.     

A Stochastic Model with Penalized Coefficients for Spatial Price Comparisons: An Application to Regional Price Indexes in Italy

This paper focuses on a new strand of research that uses stochastic approach for making spatial price comparisons. We propose a novel method to account for the presence of spatial dependencies in consumer prices and consequently in price indexes by imposing penalization conditions on the estimation of traditional CPD models leading to the spatially-penalized country-product-dummy (SP-CPD) model. The paper proposes an appropriate estimation strategy, which enables us to simultaneously estimate all the parameters in the model, including the smoothing parameter of the penalization term instead of determining it externally. In order to estimate spatial price indexes for areas lacking in price data, we suggest applying the kriging methodology to the price indexes obtained from the SP-CPD model. This new approach is applied to official Italian CPI data for constructing regional spatial price indexes for 2014. The results show that price levels are higher in the Northern-Central regions than in the South.     

Productivity Dispersion and Measurement Error

Several reasons have been put forward to explain the high dispersion of productivity across establishments: quality of management, different input usage and market distortions, to name but a few. Although it is acknowledged that a sizable portion of productivity dispersion may also be due to measurement error, little research has been devoted to identifying how much they contribute. We outline a novel procedure for identifying the role of measurement error in explaining the empirical dispersion of productivity across establishments. The starting point of our framework is the errors-in-variable model consisting of a measurement equation and a structural equation for latent productivity. We estimate the variance of the measurement error and subsequently estimate the variance of the latent productivity variable, which is not contaminated by measurement error. Using Norwegian data on the manufacture of food products, we find that about one percent of the measured dispersion stems from measurement error.     

数字普惠金融对地方税收影响的实证研究

采用北京大学测度的2011—2018年数字普惠金融指数与地方税收面板数据，研究了数字普惠金融发展与地方税收之间的关系。研究发现，数字普惠金融能够显著地促进地方税收增长，在考虑了内生性等因素后，这一结论仍然稳健地成立。分位数回归表明，数字普惠金融在低分位数上对地方税收影响小且统计显著性弱，在高分位数上数字普惠金融对地方税收的影响大且统计显著性强。数字普惠金融对地方税收的影响存在门槛效应，在不同发展阶段，其对地方税收影响有显著差异。数字普惠金融促进税收增长主要是通过数字普惠金融覆盖广度提高和移动化、便利化等程度加深实现的。     

丝绸之路河西走廊物流业效率演化分析

构建了分析河西走廊物流业效率演化的指标体系,基于2009-2017年河西走廊物流业统计数据,运用DEA-Malmquist指数法测算了各市物流业效率和技术进步率,采用Tobit回归模型分析了该地区物流业效率的影响因素,并从省内、省域间、各经济区域间三个方面进行了对比分析。实证分析表明,相较于全国各省市地区,河西走廊物流业整体水平较低,物流业效率和技术进步率的强正相关性普遍存在,其物流业发展对政策偏向具有较强的依赖性;同时,技术进步率低下和基础设施匮乏也是制约物流业发展的重要因素。基于此,从政策照顾与资金投入、科技进步与管理水平和市场运营与体系建设三个方面,为河西走廊物流业发展提出了建议与改善措施。     

Happiness sentiments and the prediction of cross-border country exchange-traded fund returns

This research examines whether social media (Twitter) happiness sentiment and country-level happiness sentiment indices predict cross-border ETF returns. To account for complicated associations between happiness sentiment and ETF returns, we use a quantile regression approach and find that Twitter and trading market (U.S.) happiness sentiments are strong predictors of future ETF returns, for which both have far greater predictive power than those of their home countries. Home country happiness indices exhibit asymmetric impacts across quantiles, suggesting the importance of trading country (U.S.) and Twitter happiness sentiments. Higher U.S. and home countries’ freedom to make life choices, absence of corruption perception, and confidence in national government precede higher ETF returns, while U.S. GDP, social support, health life expectancy, positive affect, and negative affect precede lower (abnormal) returns. We find that higher return quantile country ETFs provide a safe haven for U.S. investors during a U.S. bear market.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

The momentum and reversal effects of investor sentiment on stock prices

In this paper, we illustrate the real function relationship between the stock returns and change of investor sentiment based on the nonparametric regression model. The empirical results show that when the change of investor sentiment is moderate, the stock return is positively correlated with the change of investor sentiment, presenting an obvious momentum effect. However, the stock return is negatively correlated with the change of investor sentiment if the change of investor sentiment is dramatic, presenting significant reversal effects. Moreover, the degree of reversal effect caused by extremely optimistic sentiment is greater than that driven by extremely pessimistic sentiment, which shows a significant asymmetry. Our findings offer a partial explanation for financial anomalies such as the mean reversion of stock returns, the characteristic of slow rise and steep fall in China's stock market and so on.     

Time-varying beta in functional factor models: Evidence from China

In this paper, we introduce a functional method to investigate how betas change over time in factor models. Based on the China A-share data, we drop the constant beta assumption in the CAPM and multi-factor models to estimate the time-varying betas directly from the functional data regression. The empirical results show that exposures to all risk factors have certain time-varying patterns in the Chinese A-share stock market.