Do Spatial Price Indices Reshuffle the Italian Income Distribution?

Pittau, Maria Grazia; Zelli, Roberto; Massari, Riccardo

doi:10.4236/me.2011.23029

Cited by 6 publications

(5 citation statements)

References 6 publications

(12 reference statements)

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“…As expected, the variability within regions remained stable due to the level (regional capital city) for which local PPPs were available. Similar results were obtained byPittau et al (2011).…”

supporting

confidence: 90%

“…While considerable resources have been spent by statistical agencies for calculating PPP rates between countries, the issue of intra-national PPPs has received much less attention. Nevertheless, detailed price data required for the computation of local PPPs are not usually available at subnational level (Pittau et al 2011).…”

Section: Computation Of Local Ppps For Italymentioning

confidence: 99%

“…As in inter-country comparisons, household living standards, real income and consumption differences across sub-national areas should be evaluated by considering spatial adjustment factors which account for differences in relative price levels (Deaton et al 2004;Biggeri et al 2008). For this purpose it is essential to compute sub-national Purchasing Power Parities (PPPs) whose importance has been acknowledged by the scientific community for many years while their computation is not as widespread since the required detailed information (prices) are not usually available at sub-national level (Pittau et al 2011).…”

Section: Introductionmentioning

confidence: 99%

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Estimates of Household Consumption Expenditure at Provincial Level in Italy by Using Small Area Estimation Methods: “Real” Comparisons Using Purchasing Power Parities

Marchetti

Secondi

2016

Soc Indic Res

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Household consumption expenditure represents a crucial measure to be used for assessing individuals’ material living conditions and well-being. Indeed, the analysis of household conditions can provide policy makers with a clear picture of the economic and social situation of the area in which they are operating. However, official sample surveys which are generally used for this purpose, such as the Household Budget Survey in Italy carried out by the National Institute of Statistics, do not allow for reliable disaggregated estimates thus hindering appropriate and effective planning and evaluation of political interventions at local level. By referring to the 2012 Italian Household Budget Survey, this paper aims at obtaining reliable provincial estimates of household consumption expendi- ture in Italy. We use Small Area Estimation methods and we adjust the estimates for spatial differences in price levels by computing and using sub-national Purchasing Power Parities, thus obtaining ‘‘real’’ estimates of consumption expenditure to be used for intra-national comparisons

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supporting

confidence: 90%

Section: Computation Of Local Ppps For Italymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimates of Household Consumption Expenditure at Provincial Level in Italy by Using Small Area Estimation Methods: “Real” Comparisons Using Purchasing Power Parities

Marchetti

Secondi

2016

Soc Indic Res

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“…Some authors favour the adjustment of ARoP rates by excluding housing costs (rent and mortgage interest) from disposable income (e.g. Aaberg et al., 2008; Pittau et al., 2011). The rationale for this change is that housing costs are the most significant component of regional differences in the cost of living within countries, and that excluding them is a way to ‘level the playing field’ between the regions.…”

Section: The Arop Rate As An Indicatormentioning

confidence: 99%

Regional poverty mapping in Europe – Challenges, advances, benefits and limitations

Copus

Melo

Kaup

et al. 2015

Local Economy: The Journal of the Local Economy Policy Unit

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The 'at-risk-of-poverty' rate is the most widely recognised indicator of income poverty. Its principal advantage is that it is relatively straightforward to define and (given appropriate data) to calculate. National at-risk-of-poverty rates play a key role in monitoring EU2020 objectives relating to combating poverty. Regional patterns of poverty have the potential to deepen our understanding of processes of impoverishment and differentiation, and how they can be more effectively addressed by policy. Estimating regional poverty rates, and especially producing a European map, is a challenging task, given current data resources. This paper begins by placing the at-risk-of-poverty rate within the wider conceptual context relating to poverty, social exclusion and deprivation. It then provides an account of an exercise to map at-risk-of-poverty rates at NUTS 3 across 20 European countries. Together with data derived from national registers (where available) and more direct apportionment methods, coverage of most of Western Europe is achieved. The patterns revealed are described, and generalisations, which serve as pointers to Downloaded from further research on the processes responsible, are derived. The paper concludes with some reflections on the value of regional at-risk-of-poverty rates in advancing our understanding of the distribution and causes of poverty, and hence appropriate interventions to ameliorate it.

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“…Both phenomena could affect our measure of PED by showing more people with low income than the actual value. However, a study found that price differentials do not compensate for the differences in incomes, although they reduced the north-south gradient [ 40 ]. Regardless of all, the threshold we used of € 10,000 per year is very low, and gross incomes lower than this threshold are hardly considered adequate for living in any part of Italy.…”

Section: Discussionmentioning

confidence: 99%

SARS-CoV-2 spread and area economic disadvantage in the italian three-tier restrictions: a multilevel approach

Bardi

Acampora²,

Cacciani³

et al. 2023

BMC Public Health

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Background To face the second wave of COVID-19, Italy implemented a tiered restriction system with different limitation levels (yellow = medium; orange = medium-high, red = high) at the beginning of November 2020. The restrictions systematically reduced the transmission of SARS-CoV-2 with increasing strength for increasing tier. However, it is unknown whether the effect of limitations was equal between provinces with different socioeconomic levels. Therefore, we investigated the association between the province’s socioeconomic level and SARS-CoV-2 infection daily reproduction number in each restriction level. Methods We measured the province’s socioeconomic level as the percentage of individuals whose 2019 total yearly income was lower than 10,000€, using the measure as a proxy of economic disadvantage. We estimated the daily reproduction number (Rt) at the province level using the SARS-CoV-2 daily incidence data from November 2020 to May 2021. We then used multilevel linear regression models with random intercepts stratified by restriction level to estimate the association between economic disadvantage and Rt. We also adjusted the analyses for potential confounders of the association between the province’s economic disadvantage and the Rt: the percentage of people with 0–5 years, the quartiles of population density, and the geographical repartition. Results Overall, we found increasing Rt in yellow (+ 0.004 p < 0.01, from Rt = 0.99 to 1.08 in three weeks) and containing effects for the orange (-0.005 p < 0.01, from Rt = 1.03 to 0.93) and the red tier (-0.014 p < 0.01, from Rt = 1.05 to 0.76). More economically disadvantaged provinces had higher Rt levels in every tier, although non-significantly in the yellow level (yellow = 0.001 p = 0.19; orange = 0.002 p = 0.02; red = 0.004 p < 0.01). The results showed that the association between economic disadvantage and Rt differed by level of restriction. The number of days into the restriction and the economic disadvantage had statistically significant interactions in every adjusted model. Compared to better off, more economically disadvantaged provinces had slower increasing trends in yellow and steeper Rt reductions in orange, but they showed slower Rt reductions in the highest tier. Conclusion Lower tiers were more effective in more economically disadvantaged provinces, while the highest restriction level had milder effects. These results underline the importance of accounting for socioeconomic level when implementing public health measures.

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Do Spatial Price Indices Reshuffle the Italian Income Distribution?

Cited by 6 publications

References 6 publications

Estimates of Household Consumption Expenditure at Provincial Level in Italy by Using Small Area Estimation Methods: “Real” Comparisons Using Purchasing Power Parities

Estimates of Household Consumption Expenditure at Provincial Level in Italy by Using Small Area Estimation Methods: “Real” Comparisons Using Purchasing Power Parities

Regional poverty mapping in Europe – Challenges, advances, benefits and limitations

SARS-CoV-2 spread and area economic disadvantage in the italian three-tier restrictions: a multilevel approach

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