Accelerator or Brake? Cash for Clunkers, Household Liquidity, and Aggregate Demand

1. Accelerator or Brake? Cash for Clunkers, Household Liquidity, and Aggregate Demand Daniel Green MIT Sloan Brian Melzer Northwestern University Jonathan Parker MIT Sloan Arcenis Rojas Bureau of Labor Statistics Macro Financial Modeling

2. Disclaimer • The content of this presentation does not reflect the views or policies of the U.S. Bureau of Labor Statistics.

3. Overview • Common aim of fiscal policy in recessions is to stimulate household consumption • Tax rebates • Tax credits or price subsidies for purchase of durable goods • Temporary incentives can alter the timing of durable purchases and but financed purchases require liquidity and debt capacity • Do household financial constraints impede program participation? Can programs be designed to alleviate such constraints?

4. Our paper • We evaluate $3bn “Cash for Clunkers” of June 2009 • Rebate up to $4,500 for new purchase or lease with trade-in of clunker • Similar programs used in China, France, Germany, Italy, Japan, Netherlands, Portugal, South Korea, Spain, and UK • Detailed vehicle-level data to measure eligibility and subsidy • Comparison of eligible with similar but ineligible vehicles • CARS provided liquidity through an instant rebate • Sizeable rebate exceeds down payment for 70% of financed purchases • Contrasts with other Great Recession stimulus • But participation required repayment of outstanding loan

5. Our paper • Key findings: • Likelihood of purchase quadruples during program, increasing with size of economic subsidy • Household liquidity constrained take-up • Debt capacity played no measurable role • Aggregate impact – $11bn on 500k purchases – and do not reject rapid reversal (< 9 months) of prior studies • Liquidity critical in stimulus design

6. Related literature • Cash for Clunkers evaluations • Aggregate impact and reversal: Council of Economic Advisers (2009), National Highway Traffic Safety Administration (2009), Li, Linn, and Spiller (2012), Mian and Sufi (2012), Gayer and Parker (2013), Hoekstra, Puller, and West (2016) • Incidence:Busse, Knittel, Silva-Risso, and Zettlemeyer (2012) • Durable purchases and household liquidity • Tax rebate:Parker et al. (2013) • Minimum wage: Aaronson, Agarwal, and French (2009) • Tax refunds: Adams, Einav, and Levin (2009)

7. Outline • CARS program overview • Data and methodology • Results • What is the average impact of CARS? • Did take-up vary with the economic subsidy? • Did liquidity and debt capacity constrain take-up? • Aggregate impact? • Conclusions

8. Car Allowance Rebate System (CARS) • Trade in and scrap “clunker” • Fuel economy ≤ 18 MPG • Model year ≥ 1984, • Owned and insured for a year • Buy or lease new car or truck • MSRP ≤ $45,000 • MPG ≥ 22 (car) or MPG ≥ 18 (truck) • Rebate depends on improvement in fuel economy • $3,500 if 4 to 9 MPG (new car) or 2 to 4 MPG (new truck) • $4,500 if 10+ MPG (new car) or 5+ MPG (new truck)

9. Economic subsidy • Household gives up scrapped vehicle in exchange for fixed rebate value • Busse et al. (2012) no change in prices • Incidence on consumer Economic subsidy = Rebate – trade-in value CARS rebate – trade-in value Subsidy value $4,500 –$2,500 $2,000

10. CARS provided liquidity • Instant rebate available to fund purchase • Sizeable rebate: $4,500 exceeds down payment for 70% of financed purchases of new vehicles • Contrasts with contemporaneous stimulus programs • First-time homebuyer program – year-end tax credit • Energy-efficient appliance program – mail-in rebates • Key insight for studying liquidity: Participation required repayment of outstanding loan on clunker

11. Did liquidity affect take-up? Compare: vehicles for which CARS provides the same economic subsidybut a different amount of liquidity Example:CARS Payment $4,500, Clunker value $2,500 Two households: Economic subsidy: Liquidity available: • 5.7% of CARS-eligible vehicles secure outstanding debt • 7.2%of ineligible vehicles secure outstanding debt

12. CARS timeline and take-up • Law passed to authorize program and allocate funding on June 24, 2009 • Rules set and transactions submitted as of July 27, 2009 • Much faster than expected take-up • $1bn used up in a week and $2bn more authorized • Funds exhausted August 24, 2 months ahead of authorized end date • $2.85bn of credits on 680,000 transactions • Half on new vehicles produced domestically

13. Data on program take-up

14. Outline • CARS overview • Data and methodology • Results • What is the average impact of CARS? • Did take-up vary with the economic subsidy? • Did liquidity and debt capacity constrain take-up? • Aggregate impact? • Conclusions

15. Data • Consumer Expenditure Interview Survey • Household survey provides panel data gathered through four quarterly interviews • Three-month recall period • Household data • Income, assets, and liabilities • Vehicle data • Stock of vehicles + monthly purchases and disposals • Purchase price, financing, and trade-in value • Public data includes make and model year • BLS internal data include model

16. Data • Environmental Protection Agency (EPA) • Combined fuel efficiency by make, model, year, and options (e.g. drive train, transmission) • R.L. Polk • National registrations to calculate distribution of MPG (across model options) for a given make-model-year • Edmunds • Average trade-in value of vehicle by make, model, model year before CARS announced

17. CE new purchases, trade-in $3,500 or $4,500

18. CE used purchases, trade-in$3,500 or $4,500

19. Method: Differences-in-differences • Classify CE vehicles in June 2009 into treatment, control or other according to CARS eligibility rules • Note: uncertainty over model option; allocate if 75% of registrations within MPG thresholds • Other: Too valuable, old, fuel-efficient or eligibility too uncertain Clunkers Close-to-Clunkers • Value ≤ $5,000 • Model year ≥ 1985 • 12 ≤ MPG ≤ 18 • Owned 1+ years • Value ≤ $5,000 • Model year ≥ 1985 • 19 ≤ MPG ≤ 25

20. Sample balance

21. Measuring purchases • Define cumulative transactions or spending on new vehicles associated with disposal of vehicle i • Timing: match purchase to disposal in same month, then +/- one month • Multiple disposal matched to purchase allocated equally • Multiple purchases and single disposal – allocate both (same in treatment and control)

22. Regression model Average treatment effect: Heterogeneous treatment effect: X includes characteristics of vehicle i – fuel efficiency, estimated trade-in value, age – and characteristics of the household that owns vehicle i -- income

23. Outline • CARS overview • Data and methodology • Results • What is the average impact of CARS? • Did take-up vary with the economic subsidy? • Did liquidity and debt capacity constrain take-up? • Aggregate impact? • Conclusions

24. Average impact of CARS • Interpretation: 1.43 to 1.72 percent more likely to purchase a new vehicle with clunker vs. close-to-clunker • Marginal effect is 3x baseline rate among controls

25. Did subsidy affect take-up? • Program response decreasing in estimated trade-in value and increasing in economic subsidy

26. Response to subsidy

27. Liquidity critical for CARS take-up

28. CARS or omitted variables? • No difference in purchases before program • June purchase coefficient 0.21 (0.24) • Placebo period: Create same sample, treatment and control groups and estimate effects as if CARS was run in summer of 2008 • Placebo outcome: Estimate effects on the purchases of used vehicles

29. Placebo period: 2008 Positive not negative effect of debt secured by vehicle and similar to unsecured debt

30. Placebo outcome: Used purchases

31. Did debt capacity affect take-up • Many buyers use financing, so must be able to qualify for loan • Examine three measures of debt capacity • Income • Debt-to-income ratio (hypothetical with varying payment size on new loan • Mortgage leverage • Larger down payment may relax debt capacity constraint by providing collateral coverage

32. Debt capacity

33. Debt capacity results • No measurable effect of debt capacity constraints • One possible explanation is that CARS credit provided sufficient collateral coverage for even risky borrowers to secure loans • However, statistical power is limited so there may have been constraints that we are unable to detect (measurement error in income and debt variables?)

34. Aggregate (partial-equilibrium) impact • CE: 35,423,323 CARS-eligible w/ value below $5,500 • CARS caused 506,553 new sales in Q3 2009 (CE) • Average new car price: CE: $22,283, NHTSA: is $22,453 • $22,283 * 506,553 = $11.2 billion; Gov’t cost $3b • NHTSA: half of vehicles produced domestically • In Q3 2009 CARS raised PCE durable goods by $45 billion, imports by $22.5 billion (at annual rates) • Recession ended in Q3 2009 • In Q2 2009 GDP fell by $44 billion and in Q3 2009 GDP rose by $44 billion

35. Related Aggregate Impact Studies • Mian and Sufi (2012): compare across cities • Less precise categorization of clunker, non-clunkers • Larger estimate but assume CARS had zero effect at bottom decile of CARS-eligible share cities) • Transitory effect on cumulative vehicle sales • Hoekstra, Puller and West (2014): Administrative data in Texas • Pure regression discontinuity at 18 MPG cutoff • 18 MPG vehicles have limited choice of new vehicles for $4,500 credit • Confirms transitory effect on cumulative vehicle sales • CEA (2009) • Time series fluctuation =>Smaller estimates of CARS on sales • Li, Lin, and Spiller (2012) • Canada as control: roughly our estimate of effect of CARS • NHTSA (2009b) • Asks households who bought because of CARS

36. Outline • CARS overview • Data and methodology • Results • What is the average impact of CARS? • Did take-up vary with the economic subsidy? • Did liquidity and debt capacity constrain take-up? • Aggregate impact? • Conclusions

37. Implications for stimulus programs • Providing liquidity crucial to maximize impact of fiscal stimulus and deliver subsidy equitable to households with varying liquidity • Credit large enough to fund down payment • Credit immediately available • Raising rebate above typical down payment may generate smaller marginal response • Debt capacity less important, conditional on credit large enough to fund typical down payment • Note: this held even after financial crisis, as lenders tightened underwriting and households de-levered

38. Conclusions Credit is a major determinant of consumer spending • CARS had large bang for the buck • $11bn in sales (half domestically produced) for $3bn in Federal expenditures • But transitory: only optimal if multiplier 2009Q3>> multiplier 2010Q1 • Because take-up was highly responsive to liquidity • Vehicles securing loans much less likely to be used • Debt capacity: low power, but . . . • Most responses for middle income and middle asset households (stat weak) • Lowest response for middle debt capacity or leverage • Liquidity important consideration in programs designed to stimulate purchases of durables