Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
MTZ-Fachkongress

Antriebe und Energiesysteme von morgen


Austausch von Automobil- und Energiewirtschaft

Am 14./15. Mai geht es in Chemnitz um die Mobilitätswende durch Elektro- und Wasserstofffahrzeuge.
Erweiterte Suche
Anmelden
nach oben
Social Indicators Research
Erschienen in: Social Indicators Research 1/2016

07.07.2015

On Italian Households’ Economic Inadequacy Using Quali-Quantitative Measures

verfasst von: Luca Zanin

Erschienen in: Social Indicators Research | Ausgabe 1/2016

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Motivated by an interest in investigating factors associated with poverty risks in Italy, our study provides insight into the relationship between various socio-economic, demographic, and behavioural variables and a new measure of the economic inadequacy of households. We propose that a household is in a condition of economic inadequacy when it simultaneously has difficulty making ends meet and is in arrears with payments of commitments for more than 90 days. To analyse the determinants of economic inadequacy, we use cross-sectional microdata collected through a structured questionnaire from a 2012 survey of household income and wealth conducted by the Bank of Italy. The results of the analysis show that the probability of economic inadequacy for Italian households is higher when the household is located in regions in southern Italy, has a low equivalent income, registers a decrease in income compared with that of a normal year, has a low liquidity ratio, pays rent for the house of residence, is over-indebted, is indebted to friends and relatives, and has an unhappy and impatient household head. We also propose constructing a composite indicator at the regional level that combines the percentage of households in relative poverty, as measured by the Italian National Institute of Statistics, and the percentage of households that we identify as existing in a condition of economic inadequacy. The composite indicator allows us to take into account some aspects of household living conditions that are not included in the measure of relative poverty.
Vorheriger Artikel Consistency and Continuity in Material and Psychosocial Adversity Among Australian Families with Young Children
Nächster Artikel The Development Hypothesis of Women Empowerment in the Millennium Development Goals Tested in the Context Women’s Access to Land in Africa

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Fußnoten
1
The poverty line is derived considering the distribution of income within the population (e.g., 60 % of the median income in Eurostat’s at-risk-of-poverty measure).
 
2
This measure is given by the sum of bank deposits, postal deposits, government securities, bonds, equity in companies (traded or not traded on the stock market), investment trusts, and so forth, valued on the 31 December 2012.
 
3
Following Rosenbaum and Rubin (1983), we employ the counterfactual framework to define the effect of the treatment (for example, household heads’ time preference) on the outcome variable (for example, economic difficulty). Each individual in the population has two potential values for the outcome: \({\texttt{economic}}\, {\texttt{difficulty} }_{{\texttt{time}}\, {\texttt{preference}}=1} \) and \({\texttt{economic}}\, {\texttt{difficulty} }_{{\texttt{time}} \, {\texttt{preference}}=0} \). Obviously, we are able to observe only one of these values for each individual; the other outcome is the counterfactual. The treatment effect is therefore defined as
$${\mathbb{E}}({\texttt{economic}} \, {\texttt{difficulty}}_{{\texttt{time}} \, {\texttt{preference}}=1})-{\mathbb{E}} ({\texttt{economic}} \, {\texttt{difficulty}}_{{\texttt{time}}\, {\texttt{preference}}=0} ), $$
where effect is for the entire population. However, we are interested in the effect calculated considering only individuals who received the treatment (in our case, an individual with a high time preference); hence, we are interested in the so-called ATT (Wooldridge 2010). Let \({\mathbb{E}} ({\texttt{economic}} \, {\texttt{difficulty}} _{{\texttt{time}} \, {\texttt{preference}}=1} |{\texttt{time}} \,{\texttt{preference}}=1)\) be the average outcome of individuals when they actually manifest a high time preference, and let \({\mathbb {E}}({\texttt{economic}} \,{\texttt{difficulty} }_{{\texttt{time}} \,{\texttt{preference}} =0} |{\texttt{time}} \,{\texttt{preference }}=1)\) be the average outcome of individuals with a high time preference who are assumed not to have a high time preference. Thus, the ATT is defined as
$$\begin{aligned} {\text{ATT}} &= {\mathbb{E}} ({\texttt{economic}} \,{\texttt{difficulty}}_{{\texttt{time}}\,{\texttt{preference}}=1} |{\texttt{time}} \,{\texttt{preference }}=1)\\ &-{\mathbb{E}} ({\texttt{economic}}\, {\texttt{difficulty}}_{{\texttt{time}}\, {\texttt{preference}}=0} | {\texttt{time}}\, {\texttt{preference}}=1). \end{aligned}$$
Since \({\texttt{economic}}\, {\texttt{difficulty} }_{{\texttt{time}}\,{\texttt{preference=}}0 }\) is not observed for individuals with a high time preference, the quantity \({\mathbb {E}}({\texttt{economic}} \, {\texttt{difficulty}}_{{\texttt{time}}\, {\texttt{preference}}=0} |{\texttt{time}} \,{\texttt{preference }}=1)\) must be estimated by using the proposed RBP model (4). For further methodological details, see also Radice et al. (2013) and Zanin (2014a, b).
 
Literatur
Addabbo, T., & Baldini, M. (2000). Poverty dynamics and social transfers in Italy in the early 1990s. International Journal of Manpower, 21, 291–321.
Anderloni, L., Bacchiocchi, E., & Vandone, D. (2012). Household financial vulnerability: An empirical analysis. Research in Economics, 66, 284–296.CrossRef
Baltagi, B. H. (2002). Econometrics. New York: Springer.
Banks, J., & Johnson, P. (1994). Equivalence scale relativities revisited. The Economic Journal, 104, 883–890.CrossRef
Becker, G. S., & Mulligan, C. B. (1997). The endogenous determination of time preference. The Quarterly Journal of Economics, 3, 729–758.CrossRef
Borghans, L., Duckworth, A. L., Heckman, J. J., & Weel, B. (2008). The economics and psychology of personality traits. The Journal of Human Resources, 43, 972–1059.
Booth, A., & Amato, P. R. (2001). Parental pre-divorce relations an offspring post-divorce well-being. Journal of Marriage and Family, 3, 197–212.CrossRef
Bryant, W. K., & Zick, C. D. (2006). The economic organization of the household. New York: Cambridge University Press.
Busseri, M. A. (2012). How dispositional optimists and pessimists evaluate their past, present, and anticipated future life satisfaction: A lifespan approach. European Journal of Personality, 27, 185–199.CrossRef
Busseri, M. A., Malinowski, A., & Choma, B. L. (2013). Are optimists oriented uniquely toward the future? Investigating dispositional optimism from a temporally-expanded perspective. Journal of Research in Personality, 47, 533–538.CrossRef
Celidoni, M. (2015). Decomposing vulnerability to poverty. The Review of Income and Wealth, 61, 59–74.CrossRef
Chib, S., Greenberg, E., & Jeliazkov, I. (2009). Estimation of semiparametric models in the presence of endogeneity and sample selection. Journal of Computational and Graphical Statistics, 18, 321–348.CrossRef
Compton, J. (2009). Why do smokers divorce? Time preference and marital stability. Working Paper, Department of Economics, University of Manitoba, Manitoba.
Cracolici, M. F., Cuffaro, M., & Nijkamp, P. (2009). A spatial analysis on Italian unemployment differences. Statistical Methods & Application, 18, 275–291.CrossRef
D’Antonio, M., & Scarlato, M. (2008). Centre and periphery in development policy for the south. Review of Economics Conditions in Italy, 2, 213–243.
De Oliveira, A. C. M., Eckel, C. C., & Croson, R. T. A. (2014). Solidarity among the poor. Economics Letters, 123, 144–148.CrossRef
De Vos, K., & Zaidi, M. A. (1997). Equivalence scale sensitivity of poverty statistics for the member states of the European community. Review of Income and Wealth, 43, 319–333.CrossRef
De Vaney, S. A. (1994). The usefulness of financial ratios as predictors of household insolvency: Two perspectives. Financial Counseling and Planning, 5, 5–26.
De Vaney, S. A., & Lytton, R. (1995). Household insolvency: A review of household debt repayment, delinquency, and bankruptcy. Financial Services Review, 4, 137–156.CrossRef
Dominy, N., & Kempson, E. (2003). Can’t pay or won’t pay? A review of creditor and debtor approaches to the non-payment of bills. Working paper no. 4/03, Personal Finance Research Centre, University of Bristol.
Duygan, B., & Grant, C. (2006). Household arrears: What role do institutions play? Working paper.
Duygan, B., & Grant, C. (2009). Household debt repayment behaviour: What role do institutions play? Economic Policy, 24, 10–140.
European Central Bank (ECB) (2005). Assessing the financial vulnerability of mortgage-indebted Euro area household using micro-level data. Financial Stability Review.
Fabrizi, E., Ferrante, M. R., & Pacei, S. (2014). A micro-econometric analysis of the antipoverty effect of social cash transfer in Italy. Review of Income and Wealth, 60, 323–348.CrossRef
Festerer, J. & Winter-Ebmer, R. (2000). Smoking, discount rates and returns to education. IZA working paper no 126.
Franken, I. H., Van Strien, J. W., Nijs, I., & Muris, P. (2008). Impulsivity is associated with behavioral decision-making deficits. Psychiatry Research, 158, 155–163.CrossRef
Frederick, S., Loewenstein, G., & O’donoghue, T. (2002). Time discounting and time preference: A critical review. Journal of Economic Literature, 40, 351–401.
Gallie, D., & Paugam, S. (2002). Welfare regimes and the experience of unemployment in Europe. New York: Oxford University Press.
Georgarakos, D., Haliassos, M., & Pasini, G. (2014). Household debt and social interactions. The Review of Financial Studies, 27, 1404–1433.
Giarda, E. (2013). Persistency of financial distress amongst Italian households: Evidence from dynamic models for binary panel data. Journal of Banking & Finance, 37, 3425–3434.CrossRef
Greene, W. H. (2012). Econometric analysis. New York: Prentice Hall.
Griggs, D., Stafford-Smith, M., Gaffney, O., Rockstrm, J., hmanMC, Shyam-sundar, P., et al. (2013). Policy: Sustainable development goals for people and planet. Nature, 495, 305–307.CrossRef
Hagenaars, A. J. M., De Vos, K., & Zaidi, M. A. (1994). Poverty statistics in the late 1980s: Research based on micro-data. Technical report, Office for Official Publications of the European Communities, Luxembourg.
Helliwell, J. F., & Putnam, R. D. (1995). Economic growth and social capital in Italy. Eastern Economic Journal, 21, 295–307.
Helliwell, J. F. & Grover, S. (2014). How’s life at home? New evidence on marriage and the set point for happiness. NBER working paper no 20794
Hick, R. (2014). On ‘consistent’ poverty. Social Indicators Research, 118, 1087–1102.CrossRef
Holden, S. T., Shiferaw, B., & Wik, M. (1998). Poverty, market imperfections and time preferences: Of relevance for environmental policy? Environment and Development Economics, 3, 105–130.CrossRef
Lawrence, E. C. (1991). Poverty and the rate of time preference: Evidence from panel data. The Journal of Political Economy, 99, 54–77.CrossRef
Little, R. (1985). A note about models for selectivity bias. Econometrica, 53, 14691474.CrossRef
Litwin, H., & Sapir, E. V. (2009). Perceived income adequacy among older adults in 12 countries: Findings from the survey of health, ageing and retirement in Europe. The Gerontologist, 49, 1–10.
Lusardi, A., Schneider, D., & Tufano, P. (2011). Financially fragile household: Evidence and implications. NBER working paper no 17072.
Marra, G., Miller, D. L., & Zanin, L. (2012). Modelling the spatiotemporal distribution of the incidence of resident foreign population. Statistica Neerlandica, 66, 133–160.CrossRef
Maddala, G. S. (1983). Limited dependent and qualitative variables in econometrics. Cambridge: Cambridge University Press.CrossRef
Monfardini, C., & Radice, R. (2008). Testing exogeneity in the bivariate probit model: A Monte Carlo study. Oxford Bulletin of Economics and Statistics, 70, 271–282.CrossRef
Muffels, R. J. A. (2008). Flexibly and employment security in Europe: Labour market in transition. USA: Edward Elgar Pubblishing Limited.CrossRef
Nandori, E. S. (2014). Interpretation of poverty in St. Louis County, Minnesota. Applied Research in Quality of Life, 9, 479–503.CrossRef
Nelson, J. A. (1993). Household equivalence scales: Theory versus policy? Journal of Labor Economics, 11, 471–493.CrossRef
Kaya, O. (2014). Is perceived financial inadequacy persistent? Review of Income and Wealth, 60, 636–654.
Karlsson, N., Dellgran, P., Klingander, B., & Garling, T. (2004). Household consumption: Influences of aspiration level, social comparison, and money management. Journal of Economic Psychology, 25, 753–769.CrossRef
Komlos, J., Smith, P. K., & Barry, B. (2003). Obesity and the rate of time preference: Is there a connection? University of Munch, Discussion paper 2003-16
Radice, R., Zanin, L., & Marra, G. (2013). On the effect of obesity on employment in the presence of observed and unobserved confounders. Statistica Neerlandica, 67, 436–455.CrossRef
Rosenbaum, P., & Rubin, D. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.CrossRef
StataCorp. (2011). Stata statistical software: Release 12. College Station, TX: StataCorp LP.
Strassle, C. G., McKee, E. A., & Plant, D. D. (1999). Optimism as an indicator of psychological health: Using psychological assessment wisely. Journal of Personality Assessment, 72, 265–276.
Tu, Q. (2004). Reference points and loss aversion in intertemporal choice. Institute of World Economics and Politics, Chinese Academy of Social Sciences, Wageningen University. doi:10.​2139/​ssrn.​644142.
Weiss, A., Bates, T. C., & Luciano, M. (2008). Happiness is a personal(ity) thing: The genetics of personality and well-being in a representative sample. Psychological Science, 19, 205–210.CrossRef
Wilde, J. (2000). Identification of multiple equation probit models with endogenous dummy regressors. Economics Letters, 69, 309–312.
Winger, B. J., & Frasca, R. R. (1993). Personal finance: An integrated planning approach (3rd ed.). New York: Macmillan Publishing Company.
Wood, S. N. (2006). Generalized additive models: An introduction with R. London: Chapman & Hall.
Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. Cambridge: MIT Press.
Wu, J. (2010). Pleasure and meaning: The two foundations of happiness. Applied Research in Quality of Life, 5, 79–80.CrossRef
Zanin, L., & Marra, G. (2012). A comparative study of the use of generalized additive model and generalized linear models in tourism research. International Journal of Tourism Research, 14, 451–468.CrossRef
Zanin, L. (2013). Detecting unobserved heterogeneity in the relationship between subjective well-being and satisfaction in various domains of life using the REBUS-PLS path modelling approach: A case study. Social Indicators Research, 110, 281–304.CrossRef
Zanin, L., Radice, R., & Marra, G. (2014). A comparison of approaches for estimating the effect of Women’s education on the probability of using modern contraceptive methods in Malawi. The Social Science Journal, 51, 361–367.CrossRef
Zanin, L. (2014b). On Okun’s law in OECD countries: An analysis by age cohorts. Economics Letters, 125, 243–248.CrossRef
Zanin, L. (2015). The response of Italian households to a large transitory income shock during an economic crisis: An experimental study on the intention to increase consumption levels. Working paper available at SSRN: http://​ssrn.​com/​abstract=​2605746.
Metadaten
Titel
On Italian Households’ Economic Inadequacy Using Quali-Quantitative Measures
verfasst von
Luca Zanin
Publikationsdatum
07.07.2015
Verlag
Springer Netherlands
Erschienen in
Social Indicators Research / Ausgabe 1/2016
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-015-1019-1

Weitere Artikel der Ausgabe 1/2016

Social Indicators Research 1/2016 Zur Ausgabe

OriginalPaper

Stress Coping Strategies, Perceived Organizational Support and Marital Status as Predictors of Work–Life Balance among Nigerian Bank Employees

OriginalPaper

Is There a Link Between Poverty and Food Security?

OriginalPaper

The Development Hypothesis of Women Empowerment in the Millennium Development Goals Tested in the Context Women’s Access to Land in Africa

OriginalPaper

How Durable are Social Norms? Immigrant Trust and Generosity in 132 Countries

OriginalPaper

Why Economic Growth did not Translate into Increased Happiness: Preliminary Results of a Multilevel Modeling of Happiness in China

OriginalPaper

Construction, Robustness Assessment and Application of an Index of Perceived Level of Socio-Economic Threat from Immigrants: A Study of 47 European Countries and Regions

Premium Partner

    Bildnachweise