Behavioral Labor, Behavioral Macro and Behavioral Finance

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Behavioral Labor, Behavioral Macro and Behavioral Finance. David Laibson Harvard University July 7, 2014 This deck contains many hidden slides that were not shown during the summer school. Behavioral Labor. Labor economists have long been sympathetic to behavioral economics. - PowerPoint PPT Presentation

Transcript of Behavioral Labor, Behavioral Macro and Behavioral Finance

An Interpretation of the Financial Crisis

Behavioral Labor, Behavioral Macro and Behavioral FinanceDavid LaibsonHarvard University

July 7, 2014

This deck contains many hidden slides that were not shown during the summer school.1Outline

Downward nominal wage rigidityBelief Formation Asset Pricing AnomaliesBubbles and fluctuations23Psychological foundations of bubblesExtrapolation its a generally useful heuristic LaPorta (2003)Companies with high historical earnings growth have negative earnings surprisesCompanies with low historical earnings growth have positive earnings surprises34Psychological foundations of bubblesReturn chasingOne standard deviation increase in an investors idiosyncratic 401(k) rate of return during the current year increases her 401(k) savings rate at year-end by 0.13 percentage points (Choi, Laibson, Madrian, and Metrick, 2009)Depression babies avoid stocks in the 1960s and Oil shock babies avoid stocks in the 1990s (Malmendier and Nagel, 2009)Brokerage investors repurchase individual stocks they previously sold for a gain while shunning individual stocks they previously sold for a loss (Barber, Odean, and Strahilevetz, 2004)Finnish investors are more likely to subscribe to future IPOs if they experienced high returns in their prior IPO subscriptions (Kaustia and Knpfer, 2008)45Wishful thinkinge.g., Weinstein (1980) Believe optimistic scenarios if they are plausible 70% of drivers believe they are in the top 30% Good economic news is viewed uncritically and bad economic news is viewed skepticallyPsychological foundations of bubbles56Social proof: It must be right, if everyone else is doing ite.g., Asch (1954)

Solomon Asch paradigm7 male college students in the roomtask involving visual judgmentOne card contains a single lineAnother card contains three lines Psychological foundations of bubbles6

7Social proof continueda.b.c.Which line on the left is the same as the line on the right?78Social proof continuedTask: pick out the matching lineEasy task: error rate for a lone subject is $3Com = $Palm + $Other Net Assets


-$63 = (Share price of 3Com) - (1.5)*(Share price of Palm)152Real Estate in Phoenix and Las VegasJan 1987 January 2010153Long-run horizontal supply curvePhoenix


Long-run horizontal supply curvePhoenix155

Long-run horizontal supply curve8 miles156DemandBubbleDemandLong-run horizontal supply curveLR SupplySR SupplyArbitrage: Buy your house now for $400,000 or in 3 years at $300,000PriceQuantity157DemandBubbleDemandOver-shootingLR SupplySR SupplyArbitrage: Buy your house now for $400,000 or in 3 years at $200,000PriceQuantityDWL158Case-Shiller (Nominal) IndexJanuary 1987-January 2011226.8April2006May2009159

Source: S&P/Case-Shiller home price index and Bureau of Labor Statistics (Consumer Price Index).Index of Real Home Prices in Ten Major U.S. Cities (January 1987 December 2013)

Real Housing PricesSource: Robert Shiller web data161Lehmans forecasts in 2005HPA = House Price AppreciationSource: Gerardi et al (BPEA, 2008)

Household net worth divided by GDP1952 Q1 2008 Q4Source: Flow of Funds, Federal Reserve Board ; GDP, BEA ; and authors calculations163Estimates of magnitudeBalance sheets for households and non-profits record a decrement in value of $14 trillion from 2007 q3 to 2009 q1.164Estimates of magnitude(using decomposition)Stock market 2007 P/E was 27.3 and long-run historical average is 16.3. A 1/3 decline in the value of the (2007) stock market is $5 trillion.Housing price index has fallen from 226.8 to 150. A 1/3 decline in the value of the (2006) housing stock is $7 trillion.Total magnitude of the bubble: $12 trillionThis is a lower bound, since we are neglecting other asset classes (commercial real estate, privately held businesses, etc.)165How can we be sure these were bubbles?We cant.But recall Palm and 3ComAnd recall Phoenix/Las Vegas house prices.166Basic Ingredients of the Financial CrisisBubbles in housing and equitiesLeverage in household and financial sectorsGross leverage ratio of 33:1 among investment banksDown payments shrink (from 20% to 10%, or less)Consumption and Investment CycleIf US household wealth falls by $14 trillion, then its natural that consumption falls by $700 billion.Home construction plummets (due to plummeting prices and rising inventories of foreclosed homes); this alone accounts for 4% of GDPPsychological foundations of bubblesExtrapolationReturn chasingHerding (rational and irrational)OverconfidenceOver-optimism (wishful thinking)168Fuster, Hebert, and Laibson (2011)Two key assumptionsMacro fundamentals are hump-shaped.Earnings momentum in the short-run.Earnings mean reversion in the long run.TimeUnit shockLong-run trajectoryLong-run trajectoryLong-run trajectoryStart hereSecond assumption2. Agents under-estimate the degree of long-run mean reversion.

Illustration: Dynamics for Fundamentals (Earnings)TimeUnit shockTrue dynamicsStart herePerceived dynamicsSecond assumption2. Agents under-estimate the degree of long-run mean reversion.

Why? Simple models miss slow mean reversion. Fast Mean-ReversionSlow Mean- ReversionFraction of true mean reversion in forecasts59.5%0.0%Relationship between rational & actual forecast = 0.60 = 0.09Beshears, Choi, Fuster, Laibson, and Madrian (2013)Economic reasons for parsimonious modelsTradeoff between model flexibility and over-fittingTo avoid over-fitting limit number of parameters in model, kFormalizations:Akaike Information Criterion (AIC)Bayesian (Schwarz) Information Criterion (BIC)

Psychological reasons for picking simple models (which end up missing some of the mean reversion)Agents maximize efficiency of short-term predictionsAkaike Information Criterion Bayesian (Schwarz) Information CriterionRecency bias leads agents to act as if they have small samples (Malmendier and Nagel 2011)Complexity aversion Preference for tractabilityAnchoring and representativeness also lead agents to underestimate long-run mean reversion

TimeUnit shockTrue dynamicsStart herePerceived dynamicsSchematic for EconomyGood news in fundamentalsAgents over-estimate persistence of good newsAsset prices respond to this persistent good newsConsumption and investment riseUnanticipated mean reversion in fundamentalsasset price falls debt overhangconsumption falls(investment falls)Consequences of simple models that miss some of the low frequency mean reversion:Agents recognize the short-term momentum in fundamentals but miss some of the long-run mean reversionPro-cyclical excess optimism Asset returns are excessively volatile and exhibit overreactionReturns negatively predicted by lagged returns, P/E, and lnC Real economic activity has amplified cycleslnC negatively auto-correlated in medium run Equity premium is large, although long-run equity returns covary weakly with long-run consumption growthIf agents had RE, equity premium nearly vanishesRational agents should hold high equity allocations on averageAnd follow counter-cyclical asset allocation policyRelated LiteratureAdam and Marcet (2011): learning and asset pricingBarberis, Shleifer, and Vishny (1998): extrapolative dividend forecastsBarsky and De Long (1993): extrapolation and excess volatilityBenartzi (2001): extrapolation and company stockBlack (1986): noise tradersCampbell and Mankiw (1987): shocks are persistent in low-order ARIMACampbell and Shiller (1988a,b): P/E ratio and return predictabilityChoi (2006): extrapolation and asset pricingChoi, Laibson, and Madrian (2009): positive feedback in investmentCutler, Poterba, and Summers (1991): return autocorrelationsDe Long, et al (1990): noise traders and positive feedbackDe Bondt (1993): extrapolation bias in surveys and experimentsDe Bondt and Thaler (1985, 1989, 1993): over-shooting in asset prices Gabaix (2010): sparse representationsHommes (2005, 2008): bubbles in the labHong and Stein (1999): forecasting biases

Some Related LiteratureKahneman and Tversky (1973): representativenessKeynes (1936): animal spiritsLansing (2010): extrapolation and asset pricing in a macro modelLaPorta (1996): Growth expectations have insufficient mean reversionLeBaron, Arthur, and Palmer (1999): agent-based modelingLeBaron and Tesfatsion (2008): agent-based modelingLeroy and Porter (1981): excess volatility in stock pricesLettau and Ludvigson (1991): W/C correlates negatively with future returnsLo and MacKinlay (1988): variance ratio tests Loewenstein, ODonoghue, and Rabin (2003): projection biasMalmendier and Nagel (2011): Recency bias and role of personal experienceParker (2001): Cov of returns and lnC rises from short- to medium-runPiazessi and Schneider (2009): extrapolative beliefs in the housing marketPrevitero (2010): extrapolative beliefs and annuity investmentShiller (1981): excess volatility in stock pricesSummers (1986): power problems in financial econometricsTortorice (2010): extrapolative beliefs in unemployment forecasts

ModelCARA habit preferences (Alessie and Lusardi)

Dynamic budget constraint for wealth, wt

Elastic supply of foreign capital with gross return RAssume foreign agents dont hold domestic capitalHome biasMoral hazard

Growth in dividends (lnD = d) is captured by an auto-regressive model with p lags:

AR(p) model in dividend growth

Natural expectations

Data generating processNatural expectationsWe will study cases 1 p 40.Model matches the data for p 20.

Consumption is a weighted average of ct-1 and YtPermanent incomeShift term

Value function: Price of the equity tree:

U.S. Log Real Capital Income (1947q1-2010q3)U.S. NIPA (BEA): net operating surplus of private enterprises.

Perceived impulse response functions for real capital income;autoregressive model estimated with p lagsQuartersUnit