Micro Data For Macro Models

1. Micro Data For Macro Models Topic 2: Lifecycle Consumption

2. Part A:Overview of Lifecycle Expenditures

3. Why Do We Care About Lifecycle Expenditure? Why is it important? Learn about household preferences broadly C.E.S. vs. log vs. other / Habits? / Status? - Estimate preference parameters intertemporal elasticity of substitution/ risk aversion/ discount rate - Learn about income process permanent vs. transitory shocks / expected vs. unexpected - Learn about financial markets/constraints liquidity constraints / risk sharing arrangements - Learn about policy responses spending after tax rebates, fiscal multipliers, etc.

4. Why Do We Care (continued)? The big picture with consumption: - Use estimated parameters to calibrate models - Understand business cycle volatility - Conduct policy experiments (social security reform, health care reform, tax reform, etc.) - Estimate responsiveness to fiscal or monetary policy - Broadly understand household behavior

5. How We Will Proceed The outline of the next part of the lecture: - Understand lifecycle consumption movements o Illustrative of how one fact can spawn multiple theories. o Show how a little more data can refine the theories o Illustrate the empirical importance of the Beckerian consumption model (i.e, incorporating home production and leisure).

6. Fact 1: Lifecycle Expenditures Plot: Adjusted for cohort and family size fixed effects

7. Define Non-Durable Consumption (70% of outlays) • Use a measure of non-durable consumption + housing services • Non-durable consumption includes: Food (food away + food at home) Entertainment Services Alcohol and Tobacco Utilities Non-Durable Transportation Charitable Giving Clothing and Personal Care Net Gambling Receipts Domestic Services Airfare • Housing services are computed as: Actual Rent (for renters) Imputed Rent (for home owners) – Impute rent two ways • Exclude: Education (2%) , Health (6%), Non Housing Durables (16%), and Other (5%) <<where % is out of total household expenditures>>

8. Empirical Strategy: Lifecycle Profile of Expenditure • Estimate: (1) where is real expenditure on category k by household i in year t. Note: All expenditures deflated by corresponding product-level NIPA deflators. Cohortit= year-of-birth (5 year range – i.e., 1926-1930) Dt= Vector of normalized year dummies (See Hall (1968)) Family Composition Controls: Household size dummies, Number of Children Dummies Marital status dummies, Detailed Age of Children Dummies

9. Fact 2: Hump Shaped Profile – By Education From Attanasio and Weber (2009)

10. Fact 3: Retirement Consumption Dynamics From Bernheim, Skinner and Weinberg (AER 2001)

11. The Puzzle? (Friedman, Modigliani, Hall, etc.) {Nt, Vt} are permanent and transitory mean zero shocks to income with underlying variances equal to σ2N and σ2V

12. Preferences

13. Euler Equation

14. What Are Potential Taste Shifters Over Life Cycle Family Size o Makes some difference o Hump shaped pattern still persists o See Facts 1 and 3 (above) – these were estimated taking out detailed family size controls. 2. Other Taste Shifters (that change over the lifecycle – for a given individual)?

15. Fact 4: Deaton and Paxson (1994) “Intertemporal Choice and Inequality” (JPE) Hypotheses: PIH implies that for any cohort of people born at the same time, inequality in both consumption and income should grow with age. How much consumption inequality grows informs researchers about: o Lifecycle shocks to permanent income o Insurance mechanisms available to households. Data: U.S., Great Britain, and Taiwan

16. Deaton and Paxson Methodology (U.S. Application) Variance of Residual Variation Compute variance of εkitat each age and cohort Regress variance of εkiton age and cohort dummies Plot age coefficients (deviation from 25 year olds) Note: This is my application of the Deaton/Paxson Methodology (very similar in spirit to theirs).

17. Fact 4: Deaton-Paxson Cross Sectional Dispersion: With and With Out Housing Services

18. Fact 4: Deaton-Paxson Cross Sectional Dispersion: With and With Out Housing Services Cross Sectional Variance of Total Nondurables for 25 Year Olds = 0.16

19. Fact 4: Deaton-Paxson Cross Sectional Dispersion: With and With Out Housing Services Cross Sectional Variance of Total Nondurables for 25 Year Olds = 0.16

20. Questions: 1. What Else Drives the Hump Shaped Expenditure Profile? 2. Why Does Expenditures (on food) Fall Sharply At Retirement? 3. Why Does Cross Sectional Consumption Inequality Increase Over the Lifecycle?

21. Explanations for Questions (1) and/or (2) Liquidity Constraints and Impatience - Gourinchas and Parker (2002) Myopia - Keynes (and others) Time Inconsistent Preferences (with liquidity constraints) - Angeletos et al (2001) Habits and Impatience Non-Separable Preferences Between Consumption and Leisure - Heckman (1974) Home Production/Work Related Expenses - Aguiar and Hurst (2005, 2008)

22. Part B: The Beckerian Model of Consumption

23. Ghez and Becker (1975); Aguiar, Hurst and Karabarbounis (2011) subject to: (assume C.E.S., CRS) Let μ, λ, θ, andκbe the respective multipliers on the time budget constraint, the money budget constraint, the positive hours constraint and the positive assets constraint. Assume U(.) is additively separable across time and across goods. ψ= is vector of wages, commodity prices (p), taxes and transfers

24. First Order Conditions If θ= 0 (L > 0), price of time (in permanent income units) (μ/λ = w) More generally (given L often = 0), μ/λ = ω

25. First Order Conditions Intra-period tradeoff between time and goods: (1) Marginal rate of transformation between time and goods in production of n is equated to the relative price of time.

26. First Order Conditions A few assumptions: o Fi is constant elasticity of substitution o pi’s are constant over time Some algebra (2) (3) Note: To get (3), sub (2) into (1)

27. Static First Order Condition The static F.O.C. pins down expenditure relative to time inputs. If we know σ and the change in the opportunity cost of time, we should be able to pin down the relative movement in expenditures relative to time. %ΔXi -%ΔHi=σi %Δω Notice, this equation does not require us to make any assumptions about borrowing or lending, perfect foresight, etc.

28. More Intuition (Assume separability in cn’s) Differentiate FOC for xn with respect to ω holding λ constant. Get: This is just Ghez and Becker (1975) Need to compare the intra-elasticity of substitution between time and goods (σ) to the elasticity of substitution in utility across consumption goods (γ). Note: Complicates mapping of expenditures into permanent income in general and the estimation of Engel curves in particular.

29. Different Than Standard Predictions Differentiate FOC for xn with respect to ω holding λ constant. Get: Spending should fall the most (with declines in the marginal value of wealth) for goods that have high elasticities of substitution (high income elasticities).

30. Implications • For given resources (λ): • As the price of time increases, consumers substitute market goods for time (Xiincreases) – depends on σi • As the price of time increases, consumers substitute to goods (periods) in which consumption is “cheaper” (Xi falls) – depends on γi • What goods have high/low σ: - High σ: goods for which home production is an available margin of substitution (e.g., food) - Low σ: goods for which time and spending are complements (e.g., entertainment goods) • What goods have high/low γ: - High γ: goods which have a high income elasticity (luxuries) - Low γ: goods which have a low income elasticity (necessities)

31. Predictions: Lifecycle Movements Gourinchas and Parker model (and most other models) o Luxuries (entertainment) should decline more late in life relative to necessities (food) o No importance of changing opportunity cost of time over lifecycle Beckerian Model o Goods for which home production is important can move over the lifecycle in ways that are different than goods for which expenditure and time are complements. o If opportunity cost of time declines after middle age, food may decline more than entertainment later in life.

32. Part C: Tests for Beckerian Model of Consumption

33. Test 1: Aguiar and Hurst “Consumption vs. Expenditure” (JPE 2005)

34. Question What causes the decline in spending for households at the time of retirement? Bernheim, Skinner, and Weinberg (AER 2001) “What Accounts for the Variation in Retirement Wealth Among U.S. Households” o People do not plan for retirement (myopic) Banks, Blundell, and Tanner (AER 1998) “Is There a Retirement Savings Puzzle” o People get bad news (on average) at retirement (shock to λ) Hundreds of other papers documenting similar patterns for different countries. Do not think about the cost of time changing with retirement.

35. Fact 3: Retirement Consumption Dynamics From Bernheim, Skinner and Weinberg (AER 2001)

36. Our Approach: Measuring Consumption Directly Main Data Set: Continuing Survey of Food Intake of Individuals (CSFII) Conducted by Department of Agriculture Cross Sectional / Household Level Survey Two recent waves: Wave 1 (1989 -1991) ; Wave 2 (1994-1996) Nationally Representative Multi Day Interview All individuals within the household are interviewed (C at individual level) Tracks final food intake (not intermediate goods --- think about a cake) Detailed food expenditure, demographic, earnings, employment, and health measures Large sample sizes: 6,700 households in CSFII-91 8,100 households in CSFII-96 Focus on intake NOT expenditure!

37. Actual Consumption Data (CSFII) The key to the data: 24 hour food intake diaries (asked for all days in the survey) Diaries are detailed: Amount of food item consumed (detailed 8 digit food codes) Brand of food item (often unusable by researchers) Cooking method Condiments added Dept of Agriculture converts the total day’s food intake into several nutritional measures (calories, protein, saturated fat, total fat, vitamin C, riboflavin, etc.). The conversion is made using all food diary data (i.e., brand, whether cooked with butter).

38. 8 digit food codes: Cheese Example 18 of the 100 8-digit codes for cheese. 14101010 CHEESE, BLUE OR ROQUEFORT 14102010 CHEESE, BRICK 14102110 CHEESE, BRICK, W/ SALAMI 14103020 CHEESE, BRIE 14104010 CHEESE, NATURAL, CHEDDAR OR AMERICAN TYPE 14104020 CHEESE, CHEDDAR OR AMERICAN TYPE, DRY, GRATED 14104200 CHEESE, COLBY 14104250 CHEESE, COLBY JACK 14105010 CHEESE, GOUDA OR EDAM 14105200 CHEESE, GRUYERE 14106010 CHEESE, LIMBURGER 14106200 CHEESE, MONTEREY 14106500 CHEESE, MONTEREY, LOWFAT 14107010 CHEESE, MOZZARELLA, NFS (INCLUDE PIZZA CHEESE) 14107020 CHEESE, MOZZARELLA, WHOLE MILK 14107030 CHEESE, MOZZARELLA, PART SKIM (INCL ""LOWFAT"") 14107040 CHEESE, MOZZARELLA, LOW SODIUM 14107060 CHEESE, MOZZARELLA, NONFAT OR FAT FREE

39. Changes in “Spending” At Retirement Run: ln(xi) = γ0 + γ1 Retiredi + γ2 Zi + errori Retiredi is a dummy variable equal to 1 if the household head is retired. Instrument Retiredi status with age dummies (potential endogeneity) Z includes: race, sex, health, region, time, family structure controls Sample: Relatively “young” older households: Heads aged 57-71 Total food expenditure (x) falls by 17% for retired households (γ1), p-value < 0.01 Other results: Food expenditure at home falls by 15% Food expenditure away from home falls by 31%

40. Changes in “Consumption” at Retirement How do we turn these food diaries into meaningful measures of consumption? Our approach: 1. Examine Nutritional Quality of Diet (vitamins, cholesterol, fat, calories, etc.) 2. Examine individual goods with strong income elasticities (hotdogs, fruit, yogurt, shellfish, wine) 3. Luxury/Quality goods (e.g. brands vs generics, lean vs. fatty meat) 4. Use structural model to aggregate food consumption data and perform formal PIH test.

41. Nutritional Measures Regress: ln(ci) = α0 + α1 ln(yperm) + demographics <<sample: heads 25-55>> Regress: ln(ci) = β0 + β1 Retired + demographics <<sample: heads 57-71>> Consumption Measure (in logs)Estimated Elasticity (α1) Retirement Effect (β1) Calories -4% (2%) -2% (4%) Protein * -1% (1%) -3% (2%) Vitamin A * 44% (5%) 36% (9%) Vitamin C * 34% (5%) 33% (9%) Vitamin E * 18% (3%) 11% (4%) Calcium * 10% (2%) 13% (4%) Cholesterol * - 26% (3%) -9% (5%) Saturated Fat * - 9% (2%) -7% (3%) * Includes log calories as an additional control ; Include supplements as an additional control. Instrument for retirement status with age; Examined non-linear specifications (not reported) No evidence of any deterioration in diet quality

42. Some Specific Consumption Measures Regress: ci = α0 + α1 ln(yperm) + demographics <<sample: heads 25-55>> Regress: ci = β0 + β1 Retired + demographics <<sample: heads 57-71>> Consumption Measure (Dummy)Estimated Semi-ElasticityRetirement Effect Eat Fruit 0.25 (0.03) <<59%> 0.14 (0.04) Eat Yogurt 0.14 (0.02) <<8%>> 0.01 (0.03) Eat Shellfish 0.05 (0.01) <<6%>> -0.02 (0.02) Drink Wine 0.15 (0.02) <<8%>> -0.03 (0.03) Eat Oat/Rye/Multigrain Bread 0.10 (0.02) <<9%>> 0.06 (0.04) Eat Hotdog/Sausage -0.16 (0.03) <<51%>> -0.06 (0.05) Eat Ground beef -0.10 (0.03) <<22%>> -0.01 (0.04) Sample means in << >> Instrument for retirement status with age Drawback: Tastes could differ across income types Drawback: Categories are broad and do not allow for differences in quality

43. Luxury Goods/Quality: My Favorite…. Examine some dimensions of quality: Eating at restaurants with Table Service Eating Branded vs. Generic Goods Eating Lean vs. Fattier Cuts of Meat Restaurants, Brands, and Eating Lean Meat have very STRONG income elasticities in the cross section of working households. If households are unprepared for retirement, we should see them switching away from such consumption goods. No evidence of that in the data.

44. Creating a Food Intake Aggregate • Where c1, ….. cJare quantities of individual consumption categories consumed X is monthly expenditure on food θ is a vector of demographic and health controls (including education, sex, race, family composition, ect.) yperm is the household’s predicted permanent income • Estimated on a sample of 40 – 55 year old household heads where the head is working full time.

45. Thought Experiment • Permanent income is our numeraire – one unit increase in our consumption index maps into a one percent increase in permanent income. • What are we doing: We project permanent income of household i onto household i’s consumption (controlling for taste shifters). • Basically, in a statistical sense, if you tell me what you eat, I can predict your permanent income. Our consumption index is in permanent income dollars! • We also did this for households aged 25-55 who are working fulltime (results did not change). • We want to ask if households act like their permanent income has changed once they become retired.

46. Is Our Permanent Income Measure Predictive? • Projection of income on consumption and expenditure patterns • How well does consumption forecast income? • Split sample into odd and even years (again focusing only on prime age household heads working full time). • Focus only on odd years of our sample (in sample): • In sample R-square 0.53 • Food consumption on its own explain 21% of variation in income • Incremental R-square is 0.12 • Focus on even years (test out of sample): • Out of sample R-square: 0.42 • Food consumption and expenditure a fairly good predictor of income

48. A Note on the Unemployed • Unemployed, on average, should experience some decline in expenditure. • Labor studies find that the unemployed (from exogenous plant closings) have earnings that are 5-10 percent lower during the subsequent decade. • Can our methodology detect a decline in expenditures for the unemployed? • Our study is imperfect – we only have cross sectional data. • Using the panel dimension of the PSID, the unemployed experience a reduction in expenditures of about 8 percent (Stephens, 2002). We find a decline of about 15 percent (in expenditures) using our data. • In terms of actual consumption intake, we find the unemployed reduce their intake by about 6 percent.

49. Conclusions • No “Retirement Consumption Puzzle” • Technically, preferences between “consumption” and leisure are not substitutes. • Leisure goes up dramatically in retirement (we will show this in a few weeks). • Food consumption (as measured by intake) remains roughly constant (if anything it increases slightly). • However, “expenditures” and leisure could still be non-separable. • Non-separability enters through “home production”

50. Test 2: Aguiar and Hurst (2009)“Deconstructing Life Cycle Expenditure”