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The influence of decision making costs on the effectiveness of tax incentives to save

The influence of decision making costs on the effectiveness of tax incentives to save. Results from the HMRC/HMT/ESRC Joint Research Programme on Taxation Analysis. Justin van de Ven (justin.van@unimelb.edu.au), MIAESR & NIESR Martin Weale & Paolo Lucchino, NIESR. November, 2013.

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The influence of decision making costs on the effectiveness of tax incentives to save

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  1. The influence of decision making costs on the effectiveness of tax incentives to save Results from the HMRC/HMT/ESRC Joint Research Programme on Taxation Analysis Justin van de Ven (justin.van@unimelb.edu.au), MIAESR & NIESR Martin Weale & Paolo Lucchino, NIESR November, 2013

  2. Aims of the research • Facilitate use by Whitehall of current best practice methods to analyse savings and employment responses to policy • Advance our understanding of household sector savings decisions • Explore the role of decision costs as influences on responses to tax incentivised savings schemes

  3. Outline • Analysing saving and employment decisions • The Lifetime Income Distributional Analysis (LINDA) Model • Empirical analysis • The influence of decisions costs on the effectiveness of ISAs

  4. Analysing saving & employment decisions • A spectrum of behavioural assumptions detailed numerical analysis detailed statistical analysis detailed statistical analysis Back-of-an- envelope analysis formal model of behaviour – uncertainty explicitly considered very broad behavioural assumptions formal model of behaviour – poor approx. of uncertainty no formal model of behaviour

  5. LINDA: A model for Whitehall • Structural model of household consumption, labour supply, and investment decisions (van de Ven and Lucchino, 2013) • Life-cycle framework • Motivating observations (Attansio & Webber, 2010) • Resolution of puzzles • Model specifics • Microsimulation of individual households that vary over a range of characteristics • Decisions modelled at annual intervals from age 20 to 120 • Demographics explicit • Hard and soft liquidity constraints • Uncertainty over wages, employment, marital status, investment returns, and time of death Modelling effort represents current best practice in the micro-economic analysis of dynamic decision making at the household level

  6. LINDA: A model for Whitehall • Projects panel data forward and back through time from a population cross-section (WAS) • Policy relevant basis for analysis • Effort has been expended to make the model accessible to non-specialists: • Excel front-end • Summary statistics reported through Excel • Simulated panel data reported in standard format

  7. LINDA: model methodology • Preferences: • Budget constraint: • Evolution of wages:

  8. wT wT-1 wT-2 w1 hT hT-1 hT-2 h1 LINDA: model methodology time

  9. Using LINDA

  10. Using LINDA

  11. LINDA: Output

  12. LINDA: Output

  13. Empirical analysis • The innovative nature of the LINDA model has important advantages for conducting empirical analysis • see Lucchino & van de Ven (2013) • Key findings: • Intertemporal elasticity of substitution at population averages in region of 0.5. • Allowing for decision costs helps to match the model to observed rates of participation in ISAs

  14. Empirical analysis Utility price of leisure (A), experience effects (B) and labour supply

  15. Empirical analysis Discount factor(A), relative risk aversion (A), preference for bequests (B) and consumption

  16. Empirical analysis Discount factor(-A), relative risk aversion (A), preference for bequests (A) and pension participation

  17. Simulated effectiveness of ISAs • ISAs do not motivate appreciable increases in household saving, with or without decision costs • in the absence of decision costs, households are projected to invest heavily through ISAs, but off-set almost all of this saving against other wealth • decision costs reduce the scale of projected ISA investments, but leave most other effects on population averages qualitatively unchanged • the form that decision costs are assumed to take has an important influence on determining distributional responses to ISAs • van de Ven (2013)

  18. Behavioural Results Projected savings behaviour of individuals born between 1977 and 1986, by existence of ISAs and decision costs over ISA participation (£000, 2006)

  19. Behavioural Results Welfare effects of ISAs (£2006)

  20. Directions for further research • Adaptation of model framework • An on-going process • Testing alternative empirical specifications and behavioural hypotheses • Stylised forms to explore intertemporal elasticity (evidence of time variation?) • Appropriate moments for empirical identification (novelty of approach) • Form of decision costs? • Applied policy analyses

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