1. “The Income-Temperature Relationship in a Cross-Section of Countries and its Implications for Global Warming” John Horowitz University of Maryland

2. Component of survey paper: • “Econometric Evidence on the Economic Role of Climate” • Income, growth • Asset values (esp. land value) • Factor productivity • Agricultural yields • Health • Recreation • Other non-market effects?

3. Why care about econometric evidence specifically? • Problems: • What is the underlying DGP? • Economic role of climate • Is evidence from even 20 years ago relevant? • Many confounding factors • All predictions are necessarily out of sample • Benefits: • Enforces intellectual discipline

4. Income • The true variable of interest • Pathway is potentially multifaceted and subtle “Does extreme afternoon heat in west-facing [apartment] blocks alter moods?” - Editorial in The Straits Times of Singapore (2000) on whether a rash of killer-litter incidents – people being killed by flowerpots and other items being tossed out of windows – was due to high heat.

5. Income, cont. “When retired people move to a warmer state, their life expectancy rises dramatically. In fact, 8 to 15 percent of the increase in American life expectancy over the last 30 years comes from people moving to warmer climates.” (Tyler Cowen, NYTimes, January 13, 2008) • Sensitivity? • Will state-level GDP of Georgia (USA) reflect last summer’s drought?

6. Income • Existing studies: • Nordhaus (2006) • Mendelsohn et al. (2007) • Preceding literature – Distance to equator • Theil and Finke (1983), Theil and Seale (1994) • Ram (1999) • Hall and Jones (1999) • Masters and McMillan (2001) • Easterly and Levine (2003)

8. Income-Temperature Relationship • Key problem is to distinguish between historical and contemporaneous explanations. • Acemoglu-Johnson-Robinson (AER 2001): Colonial mortality  Historical institutions  Current institutions  Current GDP • Colonial mortality is closely related to climate.

9. Data • GDP per capita, PPP, $2000 (World Bank) • Averaged over 3 years, 2002-2004 • Haiti 2002-2003 • A few obvious problems: • Counts heating and cooling expenditures == Misses amenity value of climate • Misses other non-market effects

10. Data, cont. • Long-run (45 year) average TEMPERATURE in the capital city • Averaged over all monitoring stations • Weighted for missing monthly observations • Unanticipated problem: Multiple capital cities • La Paz, Jerusalem, Abuja, Islamabad, Cape Town • Heat island effect? • Any heat-island effect would likely weaken our observed relationship.

11. Temperature, cont. • Is capital city temperature representative of the country? • Presumed lower bound on estimated relationship. • If large effect exists, then why? • If small effect exists, a larger “true” effect may be masked. • Alternatives?

12. Data, cont. • SAMPLE • 100 largest (population) excluding Hong Kong • 94.7 percent of world population • 95.4 percent of World GDP • Missing GDP: Burma, Cuba, Libya, North Korea, Serbia and Montenegro • Missing Population: Afghanistan, Iraq • Missing temperature: Rwanda • Regressions on OECD countries include all OECD • Regressions using mortality data include all available countries except Singapore and Bahamas

13. SETTLER MORTALITY • Acemoglu, Johnson, and Robinson (AER 2001) plus France and U.K. from Acemoglu, Johnson, and Robinson (Working paper 2000). • Other covariates • Oil production in BTU per capita • Natural gas production in BTU per capita • Coal production in BTU per capita • Former Soviet Bloc

16. Now, add Colonial Mortality

17. Results • Colonial mortality is a strong predictor of current GDP even when we include temperature. • Temperature’s effect is diminished but still large when we control for colonial mortality • Warming of 2 degrees F leads to losses of roughly 3.5 percent of world GDP. • The contemporaneous effect of temperature is 33-45 percent of the total effect of temperature.

18. Results, cont. • No countries are predicted to benefit when we extract the historical component of the income-temperature relationship. • How representative is the set of countries with mortality data? • If contemporaneous effect is 33 percent of total, then using regression #1, warming of 2 degrees costs us 4.5 percent of world GDP.

19. Robustness • Mortality data are noisy and not available for all countries. • We estimated income-temperature using OECD only. • Note: Much less variation in the temperature variable.

21. Within-country estimates • Horowitz (work in progress) • US cities: Ln(T) coefficient = -0.55 • Nordhaus (2006) • Mendelsohn, Basist, Kurukulasuriya, and Dinar (2007)

24. Nordhaus (2006) • Construct output per km2. (G-Econ data) • Regress log output on mean temperature • With and without country fixed effects • Country fixed effects reduce coefficient by 31 percent • Regress log output on four measures of temperature, temperature squared, and other climate variables • Country fixed effects • 3 degrees C reduces output by 0.72 – 1.73 percent • Functional form problems