Survival on the Titanic: Illustrating Wald and Lagrange Multiplier Tests for Proportions and Logits

Abstract: Students are interested in lecture examples and class exercises involving data connected to the maiden voyage and the sinking of the liner Titanic. Information on the passengers and their fate can be used to explore relationships between various tests for differences in survival rates between different groups of passengers. Among the concepts the authors examined are tests for differences of proportions using a normal distribution, a chi-square test for independence, a test for the equality of two logits, and a test for the significance of the coefficient of a binary variable in logit model. The authors examined the relationship between Wald and Lagrange Multiplier test statistics and give two related examples.     

A note on spurious nonlinear regression

This paper explores the power of two tests for nonlinearity against spurious nonlinear regression. Results show that while the BDS test is susceptible to spuriousness, an approach introduced by Peña and Rodriguez [Peña, D. and Rodriguez, J., 2005, Detecting nonlinearity in time series by model selection criteria, International Journal of Forecasting 21, 731–748.] is powerful, regardless of sample size.     

我国城市化水平与区域经济增长差异实证研究

基于1989-2009年省级面板数据设定了协整模型,分析了我国城市化水平与区域经济增长的长期关系。结果显示,我国城市化水平与区域经济增长之间存在显著的正相关性,且两者之间存在长期稳定的协整关系。在总体上,城市化水平对经济增长的促进作用在不同区域间的差距较大,城市化水平对区域经济发展的影响排序依次为:东部、中部、东北部、西部。因此,在加快城市化进程中做好户籍制度改革,将有利于从根本上提高城市化水平,促进区域经济的增长,消除地区经济差距。     

Growth in a Cross-section of Cities: Location,Increasing Returns or Random Growth?

Abstract

This article analyses empirically the main existing theories on income and population city growth: increasing returns to scale, locational fundamentals and random growth. To do this we consider a large database of urban, climatological and macroeconomic data from 1,173 US cities observed in 1990 and 2000. The econometric model is robust to the presence of spatial effects. Our analysis shows the existence of increasing returns and two distinct equilibria in per-capita income and population growth. We also find important differences in the structure of productive activity, unemployment rates and geographical location between cities in low-income and high-income regimes.     

Smooth Transition ARCH Models: Estimation and Testing

In this paper, we suggest an extension of the ARCH model, the smooth-transition autoregressive conditional heteroskedasticity (STARCH) model. STARCH models endogenously allow for time-varying shifts in the parameters of the conditional variance equation. The most general form of the model that we consider is a double smooth-transition model, the STAR-STARCH model, which permits not only the conditional variance, but also the mean, to be a function of a smooth-transition term. The threshold ARCH model, the Markov-ARCH model and the standard ARCH model are special cases of our STARCH model. We also develop Lagrange multiplier tests of the hypothesis that the smooth-transition term in the conditional variance is zero. We apply our STARCH model to excess Treasury bill returns. We find some evidence of a smooth transition in excess returns, but in contrast to previous studies, we find almost no evidence of volatility persistence once we allow for smooth transitions in the conditional variance. Thus, the apparent persistence in the conditional variance reported by many researchers could be a mere statistical artifact. We conduct in-sample tests comparing STARCH models to nested competitors; these suggest that STARCH models hold promise for improved predictions. Finally, we describe further extensions of the STARCH model and suggest issues in finance to which they might profitably be applied.     

Purchasing Power Parity under Regime Shifts: An Application to Asian Countries*

This paper re‐examines the long‐run purchasing power parity (PPP) relationship for nine Asian countries relative to the USA and Japan during a period containing significant structural breaks. The relevance of considering structural breaks in PPP tests is demonstrated by utilizing the Johansen et al. (2000) procedure that allows for up to two pre‐determined structural breaks. Using conventional tests without considering breaks, one is able to reject the null of no cointegration for only four countries. The Johansen et al. procedure clearly demonstrates the importance of allowing for structural breaks and provides strong support for long‐run PPP for all the countries, regardless of the base country, except in the case of the Philippines vis‐à‐vis Japan. The Hansen–Johansen parameter constancy test indicates stability for all the countries except the Philippines relative to the USA and Malaysia relative to Japan.     

Market development and market efficiency: evidence based on nonlinear panel unit root tests

This study tests the weak form market efficiency of 32 European stock markets. Utilizing monthly data from June 2006 to June 2017, six different, newly developed nonlinear panel root tests were applied in three different groups of European markets: Frontier, Emerging and Developed. The results show that there is a meaningful relationship between different levels of economic development and the weak form market efficiency. Considering the nonlinear structure of the stock market indices, use of linear models might lead to wrong conclusions regarding market efficiency. Using several nonlinear panel root tests, the results of this study shed more light on the true data generating process of the stock market indices and more appropriately model market efficiency.     

Antibody tests: They are more important than we thought

Antibody testing is a non-pharmaceutical intervention – not recognized so far in the literature – to prevent COVID-19 contagion. I show this in a simple economic model of an epidemic in which agents choose social activity under health state uncertainty. In the model, susceptible and asymptomatic agents are more socially active when they think they might be immune. And this increased activity escalates infections, deaths, and welfare losses. Antibody testing, however, prevents this escalation by revealing that those agents are not immune. Through this mechanism, I find that antibody testing prevents about 12% of COVID-19 related deaths within 12 months.