nep-fle New Economics Papers
on Financial Literacy and Education
Issue of 2017‒08‒20
four papers chosen by
Viviana Di Giovinazzo
Università degli Studi di Milano-Bicocca

  1. The labyrinth of the informal economy: measurement strategies and impacts By Victor Adame; David Tuesta
  2. Debt and Financial Vulnerability on the Verge of Retirement By Annamaria Lusardi; Olivia S. Mitchell; Noemi Oggero
  3. Dynamics of Investor Spanning Trees Around Dot-Com Bubble By Sindhuja Ranganathan; Mikko Kivel\"a; Juho Kanniainen
  4. Quantile treatment effects of Riester participation on wealth By Ihle, Dorothee

  1. By: Victor Adame; David Tuesta
    Abstract: One of the factors of the greatest upheaval to a country’s economic prospects is the substantial presence of the informal economy. The aim of this paper is to articulate a detailed statistical approach to identify the significance of such factors by examining key econometric strategies and availing ourselves of several different samples for over 160 countries.
    Keywords: Financial Inclusion , Global , Working Paper
    JEL: O17 E26
    Date: 2017–08
  2. By: Annamaria Lusardi; Olivia S. Mitchell; Noemi Oggero
    Abstract: We analyze older individuals’ debt and financial vulnerability using data from the Health and Retirement Study (HRS) and the National Financial Capability Study (NFCS). Specifically, in the HRS we examine three different cohorts (individuals age 56–61) in 1992, 2004, and 2010 to evaluate cross-cohort changes in debt over time. We also use two waves of the NFCS (2012 and 2015) to gain additional insights into debt management and older individuals’ capacity to shield themselves against shocks. We show that recent cohorts have taken on more debt and face more financial insecurity, mostly due to having purchased more expensive homes with smaller down payments.
    JEL: D14
    Date: 2017–08
  3. By: Sindhuja Ranganathan; Mikko Kivel\"a; Juho Kanniainen
    Abstract: We identify temporal investor networks for Nokia stock by constructing networks from correlations between investor-specific net-volumes and analyze changes in the networks around dot-com bubble. We conduct the analysis separately for households, non-financial institutions, and financial institutions. Our results indicate that spanning tree measures for households reflected the boom and crisis: the maximum spanning tree measures had clear upward tendency in the bull markets when the bubble was building up, and, even more importantly, the minimum spanning tree measures pre-reacted the burst of bubble. At the same time, we find less clear reactions in minimal and maximal spanning trees of non-financial and financial institutions around the bubble, which suggest that household investors can have a greater herding tendency around bubbles.
    Date: 2017–08
  4. By: Ihle, Dorothee
    Abstract: In numerous industrialized countries the demographic change erodes the financial basis of traditional pay-as-you-go pension systems. To compensate for decreasing statutory pensions, many governments incentivize private saving by means of subsidized retirement plans. In this context, Germany introduced the so-called Riester pension plans. To assess its effectiveness, this paper analyzes the effects of participation in Riester plans on wealth at different points of the distribution. We employ an instrumental quantile regression approach using Riester eligibility as instrument for Riester participation. The analysis is based on microeconomic survey data from the German Socio-Economic Panel of wave 2012. Results suggest substantial heterogeneity in the effect of Riester participation on wealth. While Riester participation increases total net wealth in the lower tail of the conditional distribution, it does not have a significant effect on households in the middle part of the distribution. In the upper tail of the conditional asset distribution, we find negative treatment effects providing weak evidence in favor of a mere reallocation of households' asset portfolios.
    Keywords: Saving Incentives,Retirement,Wealth Distribution,Instrumental Quantile Regression
    JEL: D31 D91 I38 J32
    Date: 2017

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