College Pricing and Income Inequality

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College Pricing and Income Inequality Zhifeng Cai U of Minnesota and FRB Minneapolis Jonathan Heathcote FRB Minneapolis OSU, November 15 2016 The views expressed herein are those of the authors and not necessarily those of the Federal Reserve Bank of Minneapolis or the Federal Reserve System.

Introduction Context: Price of college tuition in U.S. has been outstripping inflation Income inequality has been rising Questions: 1. What determines tuition pricing? 2. How does rising income inequality impact: Equilibrium college pricing College attendance Key feature of theory: College is a club good Quality (desirability) of a given college depends on attributes (e.g. academic ability) of the students who attend

Theory: Related Literature Rothschild & White (1995), Ellickson, Grodal, Scotchmer, Zame (1999), Cole & Prescott (1997), Caucutt (1999), Applied: Epple & Romano (1998), Caucutt (2002), Epple, Romano & Sieg (2006, 2013), Gordon & Hedlund (2016), Jones & Yang (2014) Distinctive features of our framework: Perfectly competitive environment Large number of clubs of each type No lotteries over club membership Large number of members in each club Large number of possible club types

Trends in College Tuition 1. Average tuition has been rising 2. Tuition dispersion within schools has been rising High ability & low income students often pay less than sticker price

Tuition and Fees / All Items Price Index (BLS) 4 3.5 3 2.5 2 1.5 1 0.5 0

Tuition, Fees, Room & Board (College Board $2015) $50,000 $45,000 $40,000 $35,000 Private Sticker TFRB Private Net TFRB Public Sticker TFRB Public Net TFRB $30,000 $25,000 $20,000 $15,000 $10,000 $5,000 $0 14 15 12 13 10 11 08 09 06 07 04 05 02 03 00 01 98 99 96 97 94 95 92 93 90 91

Model: Households Continuum of measure 2 of households, each containing a parent and a college-age child Heterogeneous wrt: (i) income y, (ii) student ability a Two ability levels, indexed i {l.h}, a l < a h, measure 1 of each level Continuous distribution for income, CDF F i (y) Utility from non-durable consumption c and quality q of the college the child attends u(c, q) = log c + ϕ log(κ + q)

Household Problem Take as given tuition functions t i (q; y) Let Q denote the set of college qualities available Assume q = 0 Q, with t h (0; y) = t l (0; y) = 0 Given idiosyncratic state (y, i), solve Solution: c i (y), q i (y) max u(c, q) {c,q Q} s.t. c + t i (q; y) = y

Model: Colleges CRS technology for producing education of a given quality Quality (per student) reflects: (i) average ability of student body (ii) consumption good input (per student) e (faculty etc) q = (ηa h + (1 η)a l ) θ e 1 θ where η is share of student body that is high ability Fixed consumption cost R&B φ per student admitted

College Problem Colleges profit maximize Observe income y and child s ability type i, take as given tuition functions Choose quality level(s) to deliver, size, and input mix Input mix sub-problem for supplying mass 1 spots at q > 0 { max y h,y l,η,e t h (q; y h )η + t l (q; y l ) (1 η) e φ } s.t. q = (ηa h + (1 η) a l ) θ e 1 θ Let y h (q), y l (q), η(q), e(q) denote solution, and π(q) profit

College Problem (cont.) Define t i (q) = max y t i (q; y): no admissions at lower prices First-order conditions: ( (1 θ) ( t l (q) t h (q) ) η(q)a h + (1 η(q)) a l = q θ a ( ( (1 θ) t l (q) t h (q) ) e(q) = q θ a ( e(q) (1 θ) t l (q) t h (q) ) = η(q)a h + (1 η(q)) a l θ a Optimal size at each q: 0 if π(q) < 0 [0, ] if π(q) = 0 if π(q) > 0 ) θ 1 ) θ

Equilibrium Define χ(q): measure of students in colleges with q Q Q. Equilibrium is set of functions χ(q), t i (q), η(q), e(q), c i (y), q i (y) s.t. 1. Given t i (q), q i (y) and c i (y) solve household s problem 2. Given t i (q), η(q) and e(q) solve college s problem 3. Zero profits: Q, π(q) 0 q Q and π(q)dχ(q) = 0 Q 4. Market clearing: c i (y)df i (y)+ e(q)dχ(q)+(2 χ(0))φ = ydf i (y) i=h,l i=h,l 1 {q h (y) Q}dF h (y) = η(q)dχ(q) Q Q 1 {q l (y)=q}df l (y) = (1 η(q))dχ(q) Q Q

General Properties Tuition is independent of income: t i (q; y) = t i (q) Profit-maximizing firms don t want to give unnecessary subsidies (and could not afford to anyway) At each quality level, t h (q) < t l (q) Otherwise colleges would strictly prefer high ability students Tuition is increasing in quality: q 1 > q 2 t i (q 1 ) > t i (q 2 ) Otherwise no students would choose lower quality college Assortative matching Holding fixed ability, higher income households will choose higher quality colleges (education a normal good)

Parametric Example Pure club good model: θ = 1 q = ηa h + (1 η)a l Households sell and buy ability in college market Set ϕ = 1 u(c, q) = log c + log(κ + q) No R&B: φ = 0 Uniform income distribution: [ y U µ y y 2, µ y + ] y 2 Let µ a = a h+a l 2, a = a h a l F h (y) = F l (y)

Questions 1. What are χ(q), t h (q), t l (q)? 2. How do these objects depend on y? 3. How does market for college differ from market for fish?

Digression: Modeling College Like Fish Households endowed with a l or a h units of ability Sell and buy ability at centralized market at per unit price p Household problem: max c,q {log(c) + log(κ + q)} s.t. c + pq = y + pa i Market clearing i=h,l i=h,l c i (y)df i (y) = ydf i (y) i=h,l q i (y)df i (y) = a h + a l

Standard (Non-Club Good) Model Household FOC: Market clearing: q i (y) = y + pa i pκ 2p p = Tuition (net price) function: µ y µ a + κ t i F(q) = pq pa i = (q a i ) µ y µ a + κ 1. Dist. of ability demand depends on dist. of income 2. Net price functions are linear in q, and 3. Price function does not depend on income inequality y

The Club Good Model College distribution: Q (a l, a h ) χ (Q) = 2 ( ) 2 [ (1 η(q)) 2 + η(q) 2] 2 dq a 4 + π Q χ (a h ) = χ (a l ) = 2 4 + π = 0.28 Tuition functions: t i (q) = µ y ( q ai κ + q ) [ ( ) ] 2 y 1 arctan (1 2η(q)) 4 + π µ y Competitive equilibrium is Pareto efficient 1. Distribution of quality independent of (µ y, y, κ) 2. Price functions non-linear in q 3. Price functions depend on y

Sketch of Solution Method 1. Given any college distribution χ(q), derive income of households attending college q: y i (q; χ(.)) 2. Given y i (q; χ(.)), household s FOC gives an ODE that pins down the college tuition function: t i (q; χ(.)) dt i (q; χ(.)) dq 1 y i (q; χ(.)) t i (q; χ(.)) = 1 κ + q 3. Given t i (q; χ(.)), derive a college profit function: π(q; χ(.)) = η(q)t h (q; χ(.)) + (1 η(q))t l (q; χ(.)) 4. Solve for χ(q) from the functional equation π(q; χ(.)) = 0 This is a Volterra integral equation of the second kind with degenerate kernels, which has an analytical solution

College Distribution

Tuition

Tuition

More Properties of Club Good Equilibrium 1. Perfectly-mixed & single-ability schools set fish tuition: ( ) t i (µ a ) = tf i µa a i (µ a ) = µ y µ a + κ 2. Increasing y : t h (a h ) = t h F(a h ) = 0 t l (a l ) = t l F(a l ) = 0 raises (lowers) t l (q) for q ( ) µ a lowers (raises) t h (q) for q ( ) µ a raises tuition differential for high q, lowers diff. for low q 3. At any quality level q (0, 1) colleges will have 2 types of customer: (i) high ability with relatively low income, and (ii) low ability with relatively high income

Quantitative Example: Calibration Income distribution: Pareto Log-Normal: ln y EMG(µ i, σ 2, α) σ 2 = 0.4117 (SCF, 2007) α = 1.8 (Piketty-Saez, 2014) µ i s.t. E[y i=h ] E[y i=l ] = $67, 000 $45, 000 (avg. family income conditional on child s AFQT score being above / below median, 1997 NLSY).

Preferences and College Technology Preferences (ϕ, κ), Technology: (θ, φ) 1. Enrollment: 31.9% κ = 0.0361 2. Tuition spending to Agg. Cons.: 2.14% ϕ = 0.0409 3. Room and Board vs. Tuition and Fees φ = 0.0319 4. Peers vs. goods equally important in quality θ = 0.5 (target total 4 yr enrollment, tuition targets for private schools)

Preferences and College Technology 5. Ability gap a h a l drives within-school tuition dispersion (i) avg. sticker tuition + R&B = $41, 770 (ii) avg. price paid = $22, 900 (iii) avg. financial aid = $12, 380 institutional, $6, 490 other Assume everyone gets other aid, all institutional aid goes to high ability ave. net low ability tuition ave. net tuition a l = 0.0216 (a h = 1) = $41, 770 $6, 490 $22, 900

Calibrated Model Results 0.05 @(q) 2 log(t h (q)) 0.04 0.03 0 0.02-2 0.01 0 0 0.2 0.4 0.6 0.8 1 1.2 q -4-2.5-2 -1.5-1 -0.5 0 0.5 log(q) 0.8 log(t l (q))-log(t h (q)) 2 log(t l (q)) 0.7 0 0.6 0.5-2 0.4-2.5-2 -1.5-1 -0.5 0 0.5 log(q) -4-2.5-2 -1.5-1 -0.5 0 0.5 log(q)

Calibrated Model Results AGGREGATE LEVEL Model Data Enrollment rate 31.9% 31.9% Tuition per student / GDP pc 6.7% 6.7% Share high ability in college 48.8% Share low ability in college 15.0% INDIVIDUAL LEVEL CORRELATIONS Model corr.(college(0,1), a i ) 0.363 corr.(college(0,1), log(y)) 0.666 corr.(log(q), a i ) 0.185 corr.(log(q), log(y)) 0.905 corr.(log(t), a i ) -0.344

Model-Data Comparison Rich data on college characteristics from College Scorecard (US Dept Education) Sticker price tuition Avg. net price paid Avg. family income Avg. SAT score Avg. earnings 10 years after graduation Focus on 4 year private non-profit sector

Model Versus College Scorecard COLLEGE LEVEL STATISTCS Model Data var.(log avg. net tuition) 0.132 0.108 var.(log sticker tuition) 0.205 0.128 var.(log avg. fam income) 0.312 0.115 var.(log avg. SAT) 0.015 0.018 corr.(log net tuition, log income) 0.988 0.590 corr.(log net tuition, log SAT) 0.759 0.330 corr.(log income, log SAT) 0.844 0.580 elast. tuition wrt income 0.839 0.330

log sticker tuition & log net tuition log sticker tuition - log net tuition Sticker Price vs. Net Price Paid: Model 1 0.7 0 0.6-1 0.5-2 0.4-3 log sticker tuition log net tuition -4 0.2-2.5-2 -1.5-1 -0.5 0 0.5 log(q) 0.3

Sticker Price vs. Net Price Paid: Data 8 9 10 11 log net tuition log sticker tuition 6.4 6.6 6.8 7 7.2 7.4 log average SAT score Data source: College Scorecard, 2013-2014

Alternative Measure of Quality 8 9 10 11 12 log net tuition log sticker tuition 10 10.5 11 11.5 12 log average earnings 10 years later Data source: College Scorecard, 2013-2014

SAT versus Earnings Later in Life log average SAT score 6.4 6.6 6.8 7 7.2 7.4 10 10.5 11 11.5 12 log average earnings 10 years later Data source: College Scorecard, 2013-2014

Changing Income Inequality Conduct experiment where we move back from income distribution of 2014 to the one of 1984: α 1984 = 2.7 instead of α 2014 = 1.8 Adjust µ to hold average income fixed Also adjust ϕ to replicate 1984 enrollment rate (19.1%) ϕ 1984 = 0.025 instead of ϕ 2014 = 0.041 How large an increase in tuition does the model generate? Is higher tuition driven primarily by (i) stronger taste for college, or (ii) greater income inequality?

Calibrated Model Results 0.05 @(q) 2 log(t l (q)) 0.04 0.03 Now:,=1.8,?=0.041 Then:,=2.7,?=0.025 0 0.02 0.01-2 0 0 0.2 0.4 0.6 0.8 1 1.2 q 0.8 0.7 0.6 0.5 0.4 log(t l (q))-log(t h (q)) 0.3-2.5-2 -1.5-1 -0.5 0 0.5 log(q) -4-2.5-2 -1.5-1 -0.5 0 0.5 log(q) 2 0-2 log(t h (q)) -4-2.5-2 -1.5-1 -0.5 0 0.5 log(q)

Changes Over Time MODEL 1984 ϕ α 2014 Enrollment rate 19.1% 38.0% 16.6% 31.9% Tuition per student / GDP pc 5.6% 6.0% 6.3% 6.7% Share high ability in college 31.4% 58.9% 26.3% 48.8% var.(log avg. net tuition) 0.051 0.072 0.112 0.132 var.(log sticker tuition) 0.089 0.121 0.177 0.205 var.(log avg. fam income) 0.159 0.200 0.161 0.313 corr.(college(0,1), a i ) 0.314 0.430 0.261 0.363 corr.(log(q i ), a i ) 0.197 0.234 0.164 0.185

Key Findings 12.8 pct.pt. increase in enrollment reflects increased demand for college 19.7% increase in tuition mostly due to increased inequality More demand for college increases correlation between ability and college attendance / quality Higher income inequality reduces correlation between ability and college attendance /quality

Role of Increased Income Inequality Why does higher inequality increase tuition so much (+19.7%)? 1. rich demand higher quality colleges average college quality goes up (+11.4%) 2. marginal high ability are poorer and get priced out high ability students become scarcer and more expensive increased cost of producing quality

Conclusions Shape of income distribution affects tuition schedule in club-good model of college Rising income inequality an important factor underlying rise in average tuition Future work: make the model dynamic: (y t, a i,t ) q t (q t, a i,t ) y t+1 Γ(a i,t+1 a i,t ) Experiment with increasing the return to quality, trace out inter-generational dynamics of inequality