Endogenous Preferences Joan Walker UC Berkeley with Akshay

Endogenous Preferences Joan Walker, UC Berkeley with Akshay Vij and Feras El Zarwi December 2015 Daniel Mc. Fadden Honoris Causa Workshop @ Université de Cergy-Pontoise

Outline • Introduction – Endogenous Preferences ? • Demonstration of modeling endogenous preferences – Modality Styles in Travel Demand Models • Conclusion 2

Endogenous Preferences ? !? • Neoclassical assumption Preferences (as indicated by taste parameters & choice sets) are characteristics of the decision-maker that are exogenous to the choice situation and stable over time. • Alternatively, “The issue has never been whether or not tastes change. Rather the question is whether or not economists should concern themselves with such changes. ” – Albert and Hahnel (1990) “… economic theory proceeds largely to take wants as fixed. . . The economist has little to say about the formation of wants; this is the province of the psychologist. … The legitimacy of any justification … must rest … on the light that is shed …. ” – Friedman (1962) 3

“Where do preferences come from? Do they come from the sky? ” – Albert and Hahnel (1990) • “… we have to acknowledge and make use of the fact that preferences are partly the product of peoples’ environment. ” – von Weizsacker (1971) • “Economists have traditionally been suspicious of changing tastes, and a profession’s intellectual tastes change slowly. ” – Pollak (1978) • “… different methods of eliciting preference often give rise to systematically different ordering” – Tversky and Thaler (1990) • “If advertising increases the utility consumers received from goods that are advertised, [how] should the effect on consumer welfare be measured…? ” – Becker (1996) • “If legal rules have inevitable effects on preferences, it is hard to see how a government might even attempt to take preferences ‘as given’” – Sunstein (1993) • “The idea that values can change leads to thinking about how public policy might alter values and thereby change responses to public policies. ” – Aaron (1994) • “If preferences are affected by the policies or institutional arrangements we study, we can neither accurately predict nor coherently evaluate the likely consequences of new policies or institutions without taking account of preference endogeneity. ” – Bowles (1998) • “In short, preferences are endogenous to the environment, but formal frameworks for examining this interaction are scarce in modern economics. ” Palacios-Huerta & Santos (2004) 4

DEMONSTRATION OF MODELING ENDOGNEOUS PREFERENCES MODALITY STYLES IN TRAVEL DEMAND MODELING 5

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Models of Travel Behavior Traditional Models • Trip-based decision – Consider all transportation alternatives – Evaluate time and cost (and other) – Make rational decision Modality style Model • Higher-level decision – Lifestyles built around particular travel modes • Limited heterogeneity Vij, Carrel, Walker (2013) 7

Latent Modality Style Formulation Individual Characteristics (S) Transportation and Land Use Attributes (Z) Travel-Related Behaviors (B)

Latent Modality Style Formulation Individual Characteristics (S) Modality Style (m) Transportation and Land Use Attributes (Z) Travel-Related Behaviors (B)

Latent Modality Style Formulation Individual Characteristics (S) Modality Style (m) CLASS-MEMBERSHIP PROBABILITY that the individual has modality style m conditional on characteristics of the individual S CLASS-SPECIFIC CHOICE PROBABILITY that individual chooses behaviors B conditional on alternative attributes Z and modality style of the individual m Transportation and Land Use Attributes (Z) MARGINAL CHOICE PROBABILITY Travel-Related Behaviors (B) unconditional on modality style m

Latent Modality Style Formulation Individual Characteristics (S) Modality Style (m) Transportation and Land Use Attributes (Z) Expected benefit of each modal style (E) CLASS-MEMBERSHIP PROBABILITY that the individual has modality style m conditional on characteristics of the individual S and expected benefit of each modality style E CLASS-SPECIFIC CHOICE PROBABILITY that individual chooses behaviors B conditional on alternative attributes Z and modality style of the individual m MARGINAL CHOICE PROBABILITY Vij and Walker (2014) Travel-Related Behaviors (B) unconditional on modality style m

Latent Modality Style Formulation • Latent Modality Style Segments; each segment (m=1, … , M) has its own people and behavior – Set of transportation alternatives considered – Willingness to pay and attitudes – Demographic distributions • Data mining of travel diary data determines – Number of segments – Behavior of each segment – Demographics of each segment M for m=1, … , M 13

Example of Estimated Modality Style Segments (San Francisco Bay Area 2000 Travel and Activity Diary) 1. Inveterate Drivers 2. Car Commuters 3. Moms in Cars 4. Transit Takers 5. Multimodals 6. Empty Nesters Vij (2013) 14

Evidence of Changing Modality Styles Percentage of the Population (San Francisco Bay Area 2000 to 2012) Vij, Gorripaty, Walker (2015) 15

Evidence of Changing Modality Styles Percentage of the Population (San Francisco Bay Area 2000 to 2012) Vij, Gorripaty, Walker (2015) 16

Impact of Changing Modality Styles on Forecasts (San Francisco Bay Area to 2024) Scenarios to project beyond 2012 Modality trends revert back to 2000 levels by 2024 Modality style distribution remains constant at 2012 levels Modality trends observed from 2000 to 2012 continue, but at half the rate Vij, Gorripaty, Walker (2015) 17

Predicting Modality Trend via Integration with HMM (Santiago, Chile 2006 -2008 Journey to Work Panel) Percentage of the Population within each Modality Style 45 40 Modality Styles 35 30 Transit 1: Bus 25 Transit 2: Bus/Metro 20 15 Transit 3: Metro/Car 10 The Drivers 5 0 -2 months +3 months +10 months +20 months Introduction of Transantiago (shock) time = 0 months El Zarwi, Vij, Walker (2015) 18

Predicting Modality Trend via Integration with HMM (Santiago, Chile 2006 -2008 Journey to Work Panel) Percentage of the Population within each Modality Style 45 40 Modality Styles 35 30 Transit 1: Bus 25 Transit 2: Bus/Metro 20 15 Transit 3: Metro/Car 10 The Drivers 5 0 -2 months +3 months +10 months +20 months Introduction of Transantiago (shock) time = 0 months El Zarwi, Vij, Walker (2015) 19

Predicting Modality Trend via Integration with HMM (Santiago, Chile 2006 -2008 Journey to Work Panel) Percentage of the Population within each Modality Style 45 40 Modality Styles 35 30 Transit 1: Bus 25 Transit 2: Bus/Metro 20 15 Transit 3: Metro/Car 10 The Drivers 5 0 -2 months +3 months +10 months +20 months Introduction of Transantiago (shock) time = 0 months El Zarwi, Vij, Walker (2015) 20

Conclusion • Philosophical Question Existence and importance of endogenous preferences? • Methodological Question How to address in econometric models? • Modality Style Demonstration – Endogenous and dynamic preferences explicitly modeled Latent Class Choice Model with feedback of Expected Max Utility; Predict trends via integration with HMM – Evidence of endogenous and dynamic preferences that are vital for application