We propose tests for nonlinear serial dependence in time series under the null hypothesis of general linear dependence, in contrast to the more widely studied null hypothesis of independence. The approach is based on combining an entropy dependence metric, which possesses many desirable properties and is used as a test statistic, with a suitable extension of surrogate data methods, a class of Monte Carlo distribution-free tests for nonlinearity, and a smoothed sieve bootstrap scheme. We show how, in the same way as the autocorrelation function is used for linear models, our tests can in principle be employed to detect the lags at which a significant nonlinear relationship is present. We prove the asymptotic validity of the proposed procedures and the corresponding inferences. The small-sample performance of the tests in terms of power and size is assessed through a simulation study. Applications to real datasets of different kinds are also presented.

This article examines the determinants of household income among urban and rural areas in India and evaluates households’ performance with different characteristics in terms of poverty. It uses four rounds of data from the consumer expenditure survey (50th, 1993/1994; 55th, 1999/2000; 61st, 2004/2005; and 66th, 2009/2010) by the National Sample Survey Organization (NSSO) in the empirical section. This study consists of two main parts. In the first, it looks at the impact of the characteristics of the head of the household (age, educational level, marital status, and gender) and household characteristics (main occupational type, household size, and social status) on monthly per capita expenditure through conditional mean least squares (LS) regressions and conditional quantile regressions. Households headed by those who are older, married, belonging to lower castes, and living in less-developed states are more likely to be in poverty. In the second part, the article explores stochastic dominance rankings relative to large classes of welfare functions/preferences between pairwise sub-groups identified by the survey year, gender, social status, and occupational type of the household heads. Our results show that ‘inferior groups’ such as ‘Backward classes’, agricultural labor in rural areas, and casual labor in urban areas are vulnerable and may be targeted for poverty alleviation strategies. The first part sheds light on key determinants of household expenditure, while the second provides a picture of poverty outcomes which helps identify potential target groups for poverty-alleviation strategies.

Purpose – The purpose of this paper is to combine multidimensional welfare analysis and entropy metrics to derive not only the best relative weights but also substitution degree among different attributes to construct multidimensional indices of well-being with Chinese Household Income Project Survey 2002 data. Design/methodology/approach – The authors follow Maasoumi’s two-step measures of multivariate inequality to calculate the inequality for three social groups in China, urban residents, migrants, and rural residents. The two-step approach provides an aggregation formula which is numerically identified in this paper based on a metric entropy distance measure between the distribution of the aggregate well-being functions, on the one hand, and the distribution of the self-reported “happiness” indicator. The authors compare the differences in relative weights and substitution degree for the three groups, and link them to some institutional factors. Findings – The authors find that incorporating substitut...

We find stochastic uniform inefficiency of many widely held (active) portfolios and fund strategies relative to popular benchmarks. Uniformity provides robust findings over general classes of utility (loss) functions and unknown distribution of returns. Evidence is based on statistical tests for the null of stochastic uniform inefficiency of a given portfolio. The alternative is that there is at least one portfolio that dominates it. We derive an analytical characterization of stochastic uniform inefficiency. We give the limit distribution for the empirical test statistic, and present a practical implementation with block bootstrap for consistent estimation of p-values. Our test is asymptotically exact and performs well in Monte Carlo experiments.