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Residential Energy Literacy and
        Capitalization
    Dirk Brounen, Nils Kok, and John M. Quigley




            AREUEA Annual Meeting
            Chicago, January 7 2012
Energy consumption and the built environment
Energy dependence starts in buildings
80%
Small        improvements in buildings can have large effects
 Carbon    emissions and buildings are closely related
 70%
     – At least 30 percent of global greenhouse gas emissions stem from
 60%   buildings (construction and subsequent economic life)
     – Buildings account for 74 percent of U.S. electricity consumption
 50%
 Built environment offers largest potential for greenhouse gas abatement

40%
Impact of energy costs directly affects private consumers
30%
 Energy  costs are a large expense
20% – 10 percent of net income (in our sample)
 Salience can only increase with rising energy prices
10%

 0%
      1960              1970             1980         1990             2000

                    Energy Consumption in Buildings     Of Which Residential
Energy consumption and the built environment
Energy dependence starts in buildings
Small improvements in buildings can have large effects
   Carbon emissions and buildings are closely related
     – At least 30 percent of global greenhouse gas emissions stem from
        buildings (construction and subsequent economic life)
     – Buildings account for 74 percent of U.S. electricity consumption
   Built environment offers largest potential for greenhouse gas abatement


Impact of energy costs directly affects private consumers
   Energy costs are a large expense
     – 10 percent of net income (in our sample)
   Salience can only increase with rising energy prices
US energy demand: 37 percent from housing
 Energy efficiency debate again prominent in policy circles
    How to reduce energy consumption in the residential housing
                            market?

1. Stricter building codes and subsidizing retrofits
    – Works, but mostly for new construction, and effects are small
        • Building codes are effective at saving energy (Jacobsen and Kotchen, in
          press)
    – Fiscal tight-belting constrains subsidies

1. Stimulating market efficiency through energy labels
    – Investments in energy efficiency may lead to:
            • Save on current resources, insure against future price increases
            • Higher transaction prices
    – Labels seem to have the desired effect (Brounen and Kok, 2011)

2. Social norms and signals
    – Providing feedback (Schultz et al., 2007; Alcott, 2011)
Energy efficiency literature assumes rationality
    Commercial investors may be different from private agents
       Current policies to reduce energy consumption assume rational
        decision-making by informed investors

       That seems to hold for sophisticated investors in commercial property
            – Labels have financial implications (Eichholtz, Kok, Quigley, 2010, 2011)
            – Or maybe labels are not even necessary (Jaffee, Wallace, Stanton, 2011)

    …but recall the “energy efficiency paradox” (Jaffe and Stavins, 1994)

       What if consumers:
        –     Are not aware of their energy consumption
        –     Are not rational in their investment decisions
        –     Have “wrong” default settings

       The current literature ignores “energy literacy,” and policies may be
        based on wrong assumptions
Our contribution
  The (missing link) between policy and outcomes

       Energy awareness
                                        Financial (il)literacy
       - Do you know?
                                            Lusardi and Mitchel (2007)
       Energy literacy                      Lusardi and Tufano (2009)
       - Investment decision



                               Energy behavior
                               - Thermostat setting (level)
                               - Changing night temperature
                               (discrete choice)


• Demographics: lifestyle and family cycles
  (Fritzsche,1981; Van Raaij and
  Verhallen, 1983)                                                Energy bill
• Home characteristics                                            - Energy consumption
  (Brounen, Kok, Quigley, 2012; Costa and
  Kahn, 2011)
• Ideology and attitudes (Kahn, 2007)
Data

        Dutch National Bank Household Panel
          – CentERdata (Tilburg University)
          – Well-established panel (see, for example, Van Rooij et al., 2011)

       50 questions on:
         –   Demographics
         –   Financial background
         –   Home characteristics
         –   Residential energy consumption and literacy

       Link to recent surveys on attitude and ideology (smaller sample):
         – Personality
         – Political preferences
         – Spending behavior

        Executed in 2011, N = 1,721 (out of 2,028)
Energy Awareness and Literacy (I)




 44 percent of the respondents has “no idea”
Energy Awareness and Literacy (I)




 44 percent of the respondents has “no idea”
Regression results (logit)
Explaining energy awareness
Energy Awareness and Literacy




40 percent or the respondents does not know or makes
                   “irrational” choice
Energy Awareness and Literacy




40 percent or the respondents does not know or makes
                   “irrational” choice
Regression results (logit)
Explaining energy literacy
Energy behavior
    Thermostat settings
    Outcomes of energy awareness and literacy can be measured in
     ….behavior




     ….and consumption:

     (2)

     – Ei is the logarithm of gas consumption in euros for dwelling i
     – Di is a vector of demographic characteristics, including age and gender of the
       head of the household, household composition, education and income
     – Xi is a vector of the hedonic characteristics of building i, including dwelling
       size and period of construction
Energy behavior
    Thermostat settings
    Outcomes of energy awareness and literacy can be measured in
     ….behavior




     ….and consumption:

     (2)

     – Ei is the logarithm of gas consumption in euros for dwelling i
     – Di is a vector of demographic characteristics, including age and gender of the
       head of the household, household composition, education and income
     – Xi is a vector of the hedonic characteristics of building i, including dwelling
       size and period of construction
Regression results (II)
Behavior, demographics, and attitude
Regression results (III)
Energy conservation, home characteristics, and behavior
Conclusion and implications
Energy literacy is still low
 Small improvements in buildings can have large effects
    – Energy consumption and buildings are closely related

   Current policies to reduce energy consumption assume rational
    decision-making by informed investors

   Energy literacy among private consumers quite low (in line with general
    findings on energy literacy – Lusardi and Mitchell, 2008)
     – 44 percent of our sampled households is not aware of their utility bill
         • In this case stimulating energy savings is difficult
         • Predominantly young spenders that are poorly organized
     – 40 percent of households is not able to tradeoff short term outlays with long
       term savings
         • Less efficient investment, lower upfront costs
         • Predominantly the lower educated households
     – Raising awareness on energy consumption – providing feedback
       (“OPOWER” experiments)
Conclusion and implications
Default behavior is “wrong”
   Thermostat settings matters for the utility bill
     – High evening settings increase the bill (which is the case among the elderly
       and the wealthy)
     – Lowering the night settings substantially decreases the bill

    …but, 28 percent of the households do not lower their thermostat
    during night
     – They ignore the low hanging fruit of energy conservation
     – Comparable to “woodhead” behavior of mortgage holders (Quigley and
       Deng, 2002)
        • Energy conservation as the implicit default setting
        • Smart meter rollout offers opportunity

   Next steps: randomized field experiment
    with utilities

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Residential Energy Literacy

  • 1. Residential Energy Literacy and Capitalization Dirk Brounen, Nils Kok, and John M. Quigley AREUEA Annual Meeting Chicago, January 7 2012
  • 2. Energy consumption and the built environment Energy dependence starts in buildings 80% Small improvements in buildings can have large effects  Carbon emissions and buildings are closely related 70% – At least 30 percent of global greenhouse gas emissions stem from 60% buildings (construction and subsequent economic life) – Buildings account for 74 percent of U.S. electricity consumption 50%  Built environment offers largest potential for greenhouse gas abatement 40% Impact of energy costs directly affects private consumers 30%  Energy costs are a large expense 20% – 10 percent of net income (in our sample)  Salience can only increase with rising energy prices 10% 0% 1960 1970 1980 1990 2000 Energy Consumption in Buildings Of Which Residential
  • 3. Energy consumption and the built environment Energy dependence starts in buildings Small improvements in buildings can have large effects  Carbon emissions and buildings are closely related – At least 30 percent of global greenhouse gas emissions stem from buildings (construction and subsequent economic life) – Buildings account for 74 percent of U.S. electricity consumption  Built environment offers largest potential for greenhouse gas abatement Impact of energy costs directly affects private consumers  Energy costs are a large expense – 10 percent of net income (in our sample)  Salience can only increase with rising energy prices
  • 4. US energy demand: 37 percent from housing Energy efficiency debate again prominent in policy circles How to reduce energy consumption in the residential housing market? 1. Stricter building codes and subsidizing retrofits – Works, but mostly for new construction, and effects are small • Building codes are effective at saving energy (Jacobsen and Kotchen, in press) – Fiscal tight-belting constrains subsidies 1. Stimulating market efficiency through energy labels – Investments in energy efficiency may lead to: • Save on current resources, insure against future price increases • Higher transaction prices – Labels seem to have the desired effect (Brounen and Kok, 2011) 2. Social norms and signals – Providing feedback (Schultz et al., 2007; Alcott, 2011)
  • 5. Energy efficiency literature assumes rationality Commercial investors may be different from private agents  Current policies to reduce energy consumption assume rational decision-making by informed investors  That seems to hold for sophisticated investors in commercial property – Labels have financial implications (Eichholtz, Kok, Quigley, 2010, 2011) – Or maybe labels are not even necessary (Jaffee, Wallace, Stanton, 2011) …but recall the “energy efficiency paradox” (Jaffe and Stavins, 1994)  What if consumers: – Are not aware of their energy consumption – Are not rational in their investment decisions – Have “wrong” default settings  The current literature ignores “energy literacy,” and policies may be based on wrong assumptions
  • 6. Our contribution The (missing link) between policy and outcomes Energy awareness Financial (il)literacy - Do you know? Lusardi and Mitchel (2007) Energy literacy Lusardi and Tufano (2009) - Investment decision Energy behavior - Thermostat setting (level) - Changing night temperature (discrete choice) • Demographics: lifestyle and family cycles (Fritzsche,1981; Van Raaij and Verhallen, 1983) Energy bill • Home characteristics - Energy consumption (Brounen, Kok, Quigley, 2012; Costa and Kahn, 2011) • Ideology and attitudes (Kahn, 2007)
  • 7. Data  Dutch National Bank Household Panel – CentERdata (Tilburg University) – Well-established panel (see, for example, Van Rooij et al., 2011)  50 questions on: – Demographics – Financial background – Home characteristics – Residential energy consumption and literacy  Link to recent surveys on attitude and ideology (smaller sample): – Personality – Political preferences – Spending behavior  Executed in 2011, N = 1,721 (out of 2,028)
  • 8. Energy Awareness and Literacy (I) 44 percent of the respondents has “no idea”
  • 9. Energy Awareness and Literacy (I) 44 percent of the respondents has “no idea”
  • 11. Energy Awareness and Literacy 40 percent or the respondents does not know or makes “irrational” choice
  • 12. Energy Awareness and Literacy 40 percent or the respondents does not know or makes “irrational” choice
  • 14. Energy behavior Thermostat settings  Outcomes of energy awareness and literacy can be measured in ….behavior ….and consumption: (2) – Ei is the logarithm of gas consumption in euros for dwelling i – Di is a vector of demographic characteristics, including age and gender of the head of the household, household composition, education and income – Xi is a vector of the hedonic characteristics of building i, including dwelling size and period of construction
  • 15. Energy behavior Thermostat settings  Outcomes of energy awareness and literacy can be measured in ….behavior ….and consumption: (2) – Ei is the logarithm of gas consumption in euros for dwelling i – Di is a vector of demographic characteristics, including age and gender of the head of the household, household composition, education and income – Xi is a vector of the hedonic characteristics of building i, including dwelling size and period of construction
  • 16. Regression results (II) Behavior, demographics, and attitude
  • 17. Regression results (III) Energy conservation, home characteristics, and behavior
  • 18. Conclusion and implications Energy literacy is still low  Small improvements in buildings can have large effects – Energy consumption and buildings are closely related  Current policies to reduce energy consumption assume rational decision-making by informed investors  Energy literacy among private consumers quite low (in line with general findings on energy literacy – Lusardi and Mitchell, 2008) – 44 percent of our sampled households is not aware of their utility bill • In this case stimulating energy savings is difficult • Predominantly young spenders that are poorly organized – 40 percent of households is not able to tradeoff short term outlays with long term savings • Less efficient investment, lower upfront costs • Predominantly the lower educated households – Raising awareness on energy consumption – providing feedback (“OPOWER” experiments)
  • 19. Conclusion and implications Default behavior is “wrong”  Thermostat settings matters for the utility bill – High evening settings increase the bill (which is the case among the elderly and the wealthy) – Lowering the night settings substantially decreases the bill …but, 28 percent of the households do not lower their thermostat during night – They ignore the low hanging fruit of energy conservation – Comparable to “woodhead” behavior of mortgage holders (Quigley and Deng, 2002) • Energy conservation as the implicit default setting • Smart meter rollout offers opportunity  Next steps: randomized field experiment with utilities