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The Dynamics of Car Sales: A Discrete Choice Approach

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  • Jerome Adda
  • Russell Cooper

Abstract

Mankiw [1982] explores the Permanent Income Hypothesis implication that durable expenditures follow an ARMA(1,1) representation. He finds that durable expenditures are represented by an AR(1) process which implies that the rate of depreciation of durables, under the PIH model, is 100%. This finding presents a puzzle. Our paper builds on earlier work which attempts to explain this puzzle by considering the aggregation of the discrete dynamic choices of heterogeneous households. We implement this approach by estimating a dynamic discrete choice model of car replacement. We find that through aggregation we can explain both the AR and MA components of Mankiw's results. Further we find that our model is able to match a VAR representation of car sales, prices and income. We find that most of the variation in car sales is due to shocks which influence the replacement probability.

Suggested Citation

  • Jerome Adda & Russell Cooper, 2000. "The Dynamics of Car Sales: A Discrete Choice Approach," NBER Working Papers 7785, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:7785
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    Cited by:

    1. Petr Makovský, 2019. "Mankiw’s “Puzzle” – Is Durable Consumption Declining?," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 13(4), December.
    2. Ennio Stacchetti & Dmitriy Stolyarov, 2004. "Obsolescence of Durable Goods and Optimal Consumption," Econometric Society 2004 North American Summer Meetings 120, Econometric Society.
    3. Andrikopoulos, Athanasios & Markellos, Raphael N., 2015. "Dynamic interaction between markets for leasing and selling automobiles," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 260-270.
    4. Andrew Caplin & John Leahy, 2004. "How Important Is Discrete Adjustment in Aggregate Fluctuations?," NBER Chapters, in: Growth and Productivity in East Asia, pages 351-376, National Bureau of Economic Research, Inc.
    5. Brett R. Gordon, 2009. "A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry," Marketing Science, INFORMS, vol. 28(5), pages 846-867, 09-10.
    6. Yurko, Anna, 2008. "Can Increases in Real Consumer Incomes Explain the Aging of Motor Vehicles in the US?," MPRA Paper 8850, University Library of Munich, Germany, revised Apr 2008.
    7. Emmanuelle Fortune-Devlaminckx & Josef Haunschmied, 2010. "Diversity of firm’s life cycle adapted from the firm’s technology investment decision," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 18(4), pages 477-489, December.
    8. Eisfeldt, Andrea L. & Rampini, Adriano A., 2007. "New or used? Investment with credit constraints," Journal of Monetary Economics, Elsevier, vol. 54(8), pages 2656-2681, November.
    9. Enrico Moretti, 2011. "Social Learning and Peer Effects in Consumption: Evidence from Movie Sales," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 356-393.
    10. Yurko, Anna, 2008. "From Consumer Incomes to Car Ages: How the Distribution of Income Affects the Distribution of Vehicle Vintages," MPRA Paper 8849, University Library of Munich, Germany, revised Apr 2008.
    11. Heechul Min, 2015. "Korea's Cash-for-Clunkers Program: Household-Level Evidence," Asian Economic Journal, East Asian Economic Association, vol. 29(4), pages 347-363, December.
    12. Jan Bruha & Tibor Hledik & Tomas Holub & Jiri Polansky & Jaromir Tonner, 2013. "Incorporating Judgments and Dealing with Data Uncertainty in Forecasting at the Czech National Bank," Research and Policy Notes 2013/02, Czech National Bank.

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    More about this item

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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