A New Composite Lognormal-Pareto Type II Regression Model to Analyze Household Budget Data via Particle Swarm Optimization

When data exhibits heavy-tailed behavior, traditional regression approaches might be inadequate or inappropriate to model the data. In such data analyses, composite models, which are built by piecing together two or more weighted distributions at specified threshold(s), are alternative models. When data contain covariate information, composite regression models can be used. In the existing literature, there is not much work done on this topic. The only study is Gan and Valdez (2018)'s paper. In this study, a novel Lognormal-Pareto Type II composite regression model is proposed. Particle swarm optimization ( PSO ) is performed to obtain model parameters of the proposed model. The proposed model is applied to model monthly consumption expenditure and affecting factors. The data is obtained from the National Household Budget Survey, which is conducted annually by the Turkish Statistical Institute ( TurkStat ). Since the sampling design of the Household Budget Survey is stratified two-stage cluster sampling, the parameters are estimated under weighted data by updating the proposed model and PSO . Additionally, the proposed regression model performance is compared with Lognormal , Lomax , Gamma and Gamma-Pareto type II regression models. The results demonstrate that the proposed model provides an improved fit to data.

Catastrophic Expenditure on Medicines: An Analysis Based on The Portuguese Household Budget Survey 2015/2016

Financial protection is a core dimension of health system evaluation; therefore, several works on catastrophic health expenditure (CHE) have been developed. There are, however, some gaps in the literature; hence, this work aims to look at CHE from a different angle, analysing the money spent by households.

Assessing the distributional impact of lowering the value-added tax rate for standard-rated items in Tanzania and options for recouping revenue losses

This paper explores the distributional impact of lowering the value-added tax rate for standard-rated items in Tanzania Mainland. Using a static tax-benefit microsimulation model—TAZMOD—which is underpinned by data derived from the Household Budget Survey 2017/18, reductions in value-added taxes from 18 per cent to 17 per cent and 16 per cent are simulated. The revenue losses and impact on poverty are estimated. The rules for direct taxes are then modified in order to identify ways in which the revenue loss caused by the lowering of the standard rate of value-added taxes can be recouped.

Collaboration between Statistics Poland and the Institute of Social Economy in the field of social research in 1920–1939

The article presents the collaboration between Statistics Poland (GUS) and the Institute of Social Economy (IGS) in the field of social research in the period of the Second Polish Republic. On the basis of historical sources and studies it was possible to determine the scope of research undertaken by both institutions in this field and the way of organisation of their joint projects, the most important of which was the household budget survey. The smooth cooperation between the IGS and Statistics Poland was possible mostly thanks to the fact that a significant part of Statistics Poland’s managerial and research teams worked for IGS. The collaboration between both institutions yielded over one hundred publications, a majority of which concerned the social situation in Poland.

Investigating the Effects of the Household Budget Survey Redesign on Consumption and Inequality Estimates: the Italian Experience

In 2014, many innovations were introduced in the Italian Household Budget Survey (HBS) in response to changes in European recommendations and purchasing behaviours and to an increased demand for information in the context of social and economic research. New instruments and techniques have been introduced, together with more accurate methodologies, with the aim of improving the survey, by both reducing the bias and variance of survey estimates and supplying estimation for additional subpopulations and variables. Given the parallel conduction of the former and new HBS in 2013, it has been possible to evaluate the effects of the abovementioned changes on consumption expenditure and inequality estimates and to compare the sample representativeness of selected subpopulations in both surveys.

Approximation of distribution of Poland’s population’s income according to Dagum and Zenga models

The aim of this paper is to analyse the income of the population of Poland using the Dagum and the Zenga distributions. The Zenga distribution, introduced in 2010, is a new distribution which has not been yet applied to analysing wages and income in Poland. The paper presents both the Dagum and Zenga distributions, as well as the results of the approximations of wage distributions drawn from the 2014 household budget survey. The calculated degree of compliance of the theoretical distribution with the empirical one demonstrates that the Zenga distribution describes the distribution of the income of the Polish population more reliably than the Dagum distribution, which so far has been regarded as one of the best.