Optimum government size and economic growth in case of Indian states: Evidence from panel threshold model

This paper investigates the relationship between optimum government size and economic growth using data of Indian states during 1990-91 to 2017–18. Our results derived from panel threshold regression model show a positive and significant impact of government size on economic growth within the estimated thresholds for both aggregate and sub-panels based on income and regions. Once the government size moves above the upper threshold level, then its impact declines and turns to be insignificant. Thus, our findings suggest the policymakers for maintaining the government size within the thresholds limit.     

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.     

Modelling with flexibility through the business cycle: using a panel smooth transition model to test for the lipstick effect

ABSTRACT

Consumer spending typically declines during periods of economic distress, but observers have noted that lipstick purchases appear to increase during recessions, which is often referred to as the lipstick effect. However, the existence of such effect has remained empirically unconfirmed. Using weekly retail scanner data on lipstick sales from 2006 to 2016 in the United States, we applied a Panel Smooth Transition Regression (PSTR) demand model to test the relationship between economic distress and lipstick sales. This flexible demand specification allows regression coefficients to vary as a function of an exogenous macroeconomic variables and fluctuate asymmetrically, non-linearly, and time-varyingly across an unlimited number of regimes. Empirical results show the income elasticity of demand for lipstick decreased rapidly from 0.31 to 0.05 during the 2007–2009 recession, then slowly rebounded to 0.31 by the second quarter of 2014, thus first empirically confirming the existence of the lipstick effect.     

Policy uncertainty and overseas property purchases: Evidence from China

A political leadership transition occurs in China every five years. This shift in leadership is accompanied by tremendous uncertainty within Chinese society, particularly for the nation's wealthy people. Examining private residential property transaction data in Singapore, this paper reveals that the number of transactions by Chinese mainland buyers increases by half during political transitions that occurred between 1998 and 2013, in comparison to buyers from Malaysia, the US, and Hong Kong.     

Comparison of public perception and risk management decisions of aircraft noise near Taoyuan and Kaohsiung International Airports

This study uses multiple linear regression to identify factors contributing to perceived risk among residents near Taoyuan and Kaohsiung International Airports, the effect of perceived risk on their willingness to reduce risk, and consumption preferences that can reduce risk. Results indicated that residents' risk perception near Taoyuan Airport is lower than that near Kaohsiung Airport. Noise pollution experience, perceived probability of environmental contamination and negative effects, and perceived severity of catastrophic consequences significantly increase residents' perceived risks. Residents are willing to recognize and participate in mitigating the risks of aircraft noise pollution. The more risk residents perceive, the more willing they are to participate in disaster reduction and investigate means of improving the risk environment.     

The effects of news events on market contagion: Evidence from the 2007–2009 financial crisis

In this paper, we use the quantile regression technique along with coexceedance, a contagion measure, to assess the extent to which news events contribute to contagion in the stock markets during the crisis period between 2007 and 2009. Studies have shown that, not only the subprime crisis leads to a global recession, but the effects on the global stock markets have also been significant. We track the news events, both in the UK and the US, using the global recession timeline. We observe that the news events related to ad hoc bailouts of individual banks from the UK have a contagion effect throughout the period for most of the countries under investigation. This, however, is not found to be the case for the news events originating from the US. Our findings regarding the evidence of contagion effects in the UK reinforce the argument that spreads and contagion—an outcome of the risk perception of financial markets—are solely a result of the behaviour of investors or other financial market participants.     

Methods for Scalar‐on‐Function Regression

Recent years have seen an explosion of activity in the field of functional data analysis (FDA), in which curves, spectra, images and so on are considered as basic functional data units. A central problem in FDA is how to fit regression models with scalar responses and functional data points as predictors. We review some of the main approaches to this problem, categorising the basic model types as linear, non‐linear and non‐parametric. We discuss publicly available software packages and illustrate some of the procedures by application to a functional magnetic resonance imaging data set.     

Forecasting China's GDP growth using dynamic factors and mixed-frequency data

Forecasting GDP growth is important and necessary for Chinese government to set GDP growth target. To fully and efficiently utilize macroeconomic and financial information, this paper attempts to forecast China's GDP growth using dynamic predictors and mixed-frequency data. The dynamic factor model is first applied to select dynamic predictors among large amount of monthly macroeconomic and daily financial data and then the mixed data sampling regression is applied to forecast quarterly GDP growth based on the selected monthly and daily predictors. Empirical results show that forecasts using dynamic predictors and mixed-frequency data have better accuracy comparing to traditional forecasting methods. Moreover, forecasts with leads and forecast combination can further improve forecast performance.     

How to measure competition in an economy in transition

This paper attempts to find a robust method of measuring competition when firms' operational activities are subject to frictions. The first part theoretically tests the indicative quality of two competition measures, the price‐cost margin (PCM) and the profit elasticity, in a model of monopolistic competition. The second part studies the empirical performance of the indices for a panel of Ukrainian manufacturing firms. This study offers a new approach to measuring profit elasticity that relies on structural estimation of a production function. The estimation methodology retrieves a productivity index that is adjusted to imperfect competition. The proposed method of measuring profit elasticity is found to be robust to frictions, but the PCM and traditional profit elasticity are biased, especially when the intensity of competition is low. Empirical findings show that competition exhibits a significantly positive correlation with aggregate productivity performance, while its impact on firm productivity is nonlinear.     

Impacts of seasonal patterns of climate on recurrent fluctuations in tourism demand: Evidence from Aruba

This study estimates the effect of seasonal patterns of pull and push climate elements (rainfall, temperature, wind, and cloud coverage) on recurrent fluctuations in tourism demand from the United States (USA) and Venezuela to Aruba. The seasonal patterns were first isolated from the series using the Census X-12 decomposition method, after which the analysis included panel data unit root testing, panel data regression, and Euclidean distance calculation. The results show that both pull and push seasonal factors of climate were relevant in determining the seasonal variations in tourism demand from both countries. The study derives two theoretical propositions: (1) climate is a significant push and pull factor affecting tourism demand; and (2) tourism demand and climate are bounded by intertemporal climate constraints.