Climate Change, Firm Performance & Investor Surprises€¦ · Task Force Climate-Related Financial Disclosure: Climate change \one of the most signi cant, and perhaps most misunderstood,

$Page 1: Climate Change, Firm Performance & Investor Surprises€¦ · Task Force Climate-Related Financial Disclosure: Climate change \one of the most signi cant, and perhaps most misunderstood,$
Climate Change, Firm Performance & Investor Surprises

Nora M.C. Pankratz

Maastricht University, School of Business and EconomicsDepartment of Finance

Brussels, 09-01-2018


Motivation

1 Does heat exposure decrease corporate financial performance?Legislative proposals:Firms should disclose exposure to physical climate impacts.European Bank for Reconstruction and Development:Tangible metrics on first-order risks, specific references to extreme temperatures.

2 Do analysts and investors anticipate effect?Task Force Climate-Related Financial Disclosure: Climate change “one of the mostsignificant, and perhaps most misunderstood, risks that organizations face today”.

Nora M.C. Pankratz (Maastricht University) Brussels, 09-01-2018 1 / 9

Motivation




Motivation




Motivation




Example

Manufacturing firm in Central Europe.

Air conditioning not necessary given baseline climate at establishment date.

Workers are (on average) exposed to heat.

Physiology shows: increase from 25 to 30◦C decreases performance by 10%for office work (Sepannen et al., 2006).

International air conditioning rates are low (International Energy Agency, 2018).

Mechanism

Beyond labor productivity, other input prices and supply can be affected bytemperature extremes (water, electricity).

Impact on any given day is small, but compounds.


Example

Manufacturing firm in Central Europe.

Air conditioning not necessary given baseline climate at establishment date.

Workers are (on average) exposed to heat.

Physiology shows: increase from 25 to 30◦C decreases performance by 10%for office work (Sepannen et al., 2006).

International air conditioning rates are low (International Energy Agency, 2018).

Mechanism

Beyond labor productivity, other input prices and supply can be affected bytemperature extremes (water, electricity).

Impact on any given day is small, but compounds.


Preview

1 Firms are sensitive to (more days of) extremely high temperatures.

→ The negative impact will become economically substantial:10-15% loss in revenue/operating income by 2050-2100 based on IPCC projections.(but: additional assumptions)

→ Some industries and regions may benefit, but on average, the impact is negative.

2 Investors do not anticipate firm sensitivity to extreme temperatures.

a Analysts systematically overestimate performance in periods when firms wereparticularly affected.

b Announcement returns become more negative in periods when firms wereparticularly affected.

! Both tests: Information was publicly available.


Preview

1 Firms are sensitive to (more days of) extremely high temperatures.

→ The negative impact will become economically substantial:10-15% loss in revenue/operating income by 2050-2100 based on IPCC projections.(but: additional assumptions)

→ Some industries and regions may benefit, but on average, the impact is negative.

2 Investors do not anticipate firm sensitivity to extreme temperatures.

a Analysts systematically overestimate performance in periods when firms wereparticularly affected.

b Announcement returns become more negative in periods when firms wereparticularly affected.

! Both tests: Information was publicly available.


Definitions

Sample: 4,400 locally concentrated firms, 1995-2017

1 Factset Segment Reporting

2 Koeppen Classification Climate Zones

Comparable to 68% of firms on NYSE/NASDAQ, <3% market capitalization.Descriptives

Heat exposure:

1 Concept: Number of extreme temperature days in year/quarter

2 Data: Daily maximum temperatures (ERA-Interim)

3 Thresholds: 2x absolute, 2x historically derived, place/time specific Histograms

Financial performance: revenue + operating income (Compustat)

Investor surprises: analyst estimates (IBES), announcement returns (Compustat)


Definitions





Heat exposure:







Definitions





Heat exposure:







Definitions





Heat exposure:







Result (1) Extreme Temperature Exposure Decreases Financial Performance

(1) (2) (3) (4) (5) (6) (7) (8)VARIABLES Rev-Assets Rev-Assets Rev-Assets Rev-Assets OpInc-Assets OpInc-Assets OpInc-Assets OpInc-Assets

Days > 25◦C p.q. 0.00109 -0.00168(0.0099) (0.0027)

Days > 30◦C p.q. -0.02283*** -0.00314*(0.0073) (0.0018)

Days > 90 Pctl p.q. -0.01792*** -0.00276**(0.0055) (0.0013)

Days > 95 Pctl p.q. -0.01872*** -0.00320*(0.0069) (0.0018)

Observations 150,077 150,077 150,077 150,077 150,077 150,077 150,077 150,077R-squared 0.830 0.830 0.830 0.830 0.559 0.559 0.559 0.559Number Firms 4410 4410 4410 4410 4410 4410 4410 4410

Absolute and relative threshold measures negatively related to quarterly financial performance.

Economic magnitude:

� OpInc/Assets ↓ -13 to -15% of income/90 value per additional ET day.

Physiology: Experiment 25◦→ 30◦Celsius = 10% performance reduction (office, indoors).IPCC Projection




Days > 25◦C p.q. 0.00109 -0.00168(0.0099) (0.0027)

Days > 30◦C p.q. -0.02283*** -0.00314*(0.0073) (0.0018)

Days > 90 Pctl p.q. -0.01792*** -0.00276**(0.0055) (0.0013)

Days > 95 Pctl p.q. -0.01872*** -0.00320*(0.0069) (0.0018)



Economic magnitude:


Physiology: Experiment 25◦→ 30◦Celsius = 10% performance reduction (office, indoors).

IPCC Projection




Days > 25◦C p.q. 0.00109 -0.00168(0.0099) (0.0027)

Days > 30◦C p.q. -0.02283*** -0.00314*(0.0073) (0.0018)

Days > 90 Pctl p.q. -0.01792*** -0.00276**(0.0055) (0.0013)

Days > 95 Pctl p.q. -0.01872*** -0.00320*(0.0069) (0.0018)



Economic magnitude:


Physiology: Experiment 25◦→ 30◦Celsius = 10% performance reduction (office, indoors).IPCC Projection


Cross-Sectional Tests (1)

1 Mechanics

Performance mainly decreases turnover, not cost.Evidence that effect is production and not demand driven.Labor intensive firms are most sensitive.

2 Plausibility Checks

Positive impact of more extremely high temperature days incold regions & industries with heat-related demand shocks.

3 Alternative Explanations

Climate: Correlation hot and cold days does not affect the estimatesEconomy: Placebo tests - other firm-level outcomes are unaffected(e.g. cash holding, investments).



1 Mechanics








1 Mechanics








1 Mechanics







Result (2a) Earnings Surprises Decrease with Extreme Temperature Days

Hypothesis: If analysts anticipate negative impact of high temperatures, there is nosystematic relation between Extreme Temperature Days and the deviation of actualrevenue/income from analyst forecast (H0).

(A) Revenue Surprises Actual (B) Income Surprises

(1) (2) (3) (4)VARIABLES Median Median Median Median

Days > 25◦C p.q. -0.00535**(0.0023)

Days > 30◦C p.q. -0.00494*(0.0026)

Days > 90 Pctl p.q. -0.00254(0.0020)

Days > 95 Pctl p.q. -0.00182(0.0027)

Book to Market 0.00758 0.01005 0.00922 0.00921(0.0351) (0.0351) (0.0351) (0.0351)

Observations 28,580 28,580 28,580 28,580


Days > 25◦C p.q. -0.00222*(0.0012)

Days > 30◦C p.q. -0.00367***(0.0014)

Days > 90 Pctl p.q. -0.00254**(0.0012)

Days > 95 Pctl p.q. -0.00283*(0.0016)

Book to Market 0.09052*** 0.09202*** 0.09166*** 0.09209***(0.0228) (0.0229) (0.0229) (0.0229)

Observations 21,426 21,426 21,426 21,426


Result (2a) Earnings Surprises Decrease with Extreme Temperature Days

Hypothesis: If analysts anticipate negative impact of high temperatures, there is nosystematic relation between Extreme Temperature Days and the deviation of actualrevenue/income from analyst forecast (H0).

(A) Revenue Surprises Actual (B) Income Surprises


Days > 25◦C p.q. -0.00535**(0.0023)

Days > 30◦C p.q. -0.00494*(0.0026)

Days > 90 Pctl p.q. -0.00254(0.0020)

Days > 95 Pctl p.q. -0.00182(0.0027)

Book to Market 0.00758 0.01005 0.00922 0.00921(0.0351) (0.0351) (0.0351) (0.0351)

Observations 28,580 28,580 28,580 28,580


Days > 25◦C p.q. -0.00222*(0.0012)

Days > 30◦C p.q. -0.00367***(0.0014)

Days > 90 Pctl p.q. -0.00254**(0.0012)

Days > 95 Pctl p.q. -0.00283*(0.0016)

Book to Market 0.09052*** 0.09202*** 0.09166*** 0.09209***(0.0228) (0.0229) (0.0229) (0.0229)

Observations 21,426 21,426 21,426 21,426



Summary

Q1: Do extremely high temperatures influence corporate financial performance?

H0 Revenues and operating income decrease with extreme temperature days.

Expl. (B) Potentially: “Boiling frog” (Da et al., RFS 2014).

Implication Projected warming = incentive to adapt (if in firms’ control).

Q2: Do analysts and investors anticipate this relation?

H0 Analysts and investors do not fully anticipate this effect.

Explanation Slow continuous information diffusion (Da et al., RFS 2014).

Validity Similar results on U.S. data(Addoum et al., non-published working paper, in principle accept RFS).

Implication Long-term investments - To what extent do firms adapt in the long-run, andhow does this effect work if firms are geographically diversified?


Summary











Summary











Summary











IPCC ProjectionIPCC 5th Assessment Report, Figure 11.17

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IPCC ProjectionIPCC 5th Assessment Report, Figure 10.19

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Distribution of Cooling TechnologyIEA Statistics

Key findings from The Future of Cooling. Percentage of households that have AC today.Adapted from “The Future of Cooling”, International Energy Agency, 2018, retrieved from

https: // www. iea. org/ cooling/ . Copyright 2018 by the IEA and OECD.

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https://www.iea.org/cooling/

Cooling DemandWorld AC Demand

Packaged and Room Air Conditioner Demand by Region from 2012 to 2017. Adapted from “World ACDemand”, Japan Refridgeration and Air Conditioning Industry Association, 2018, retrieved from

https: // www. jraia. or. jp/ english/ World_ AC_ Demand. pdf . Copyright 2018 by the Japan Refridgeration

and Air Conditioning Industry Association. Back

https://www.jraia.or.jp/english/World_AC_Demand.pdf

Conceptual Framework, adopted from Kelly et al. (2005)Sketch

(a) Transitory Shocks (b) Permanent Trends

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Variation by Classification ThresholdsAbsolute Thresholds

Figure 1: Distribution of Days Exposed to Heat - Levels, Absolute Thresholds

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Variation by Classification ThresholdsRelative Thresholds

Figure 2: Distribution of Days Exposed to Heat - Levels, Relative Thresholds

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Industry and Region Shares

Main effect: No impact excluding agriculture, mining, manufacturing holds, retail andwholesale is particularly strong, opposite effect for utilities, services, finance - with caveatthat unusual finance composition.World Bank World Development Indicators: (agriculture 4% 2010 and 2017, droppedfrom 8.5 to 3.5 from 1995 to today, 45% Industry+Manufacturing, 60% Services).


Statistics - Sample Extreme Temperatures and Firm PerformanceDescriptives

Panel (A) Annual Data

(1) (2) (3) (4) (5) (6)VARIABLES N mean p50 sd p25 p75

Days > 25◦C p.a. 41,910.000 199.551 197.000 154.524 37.000 364.000Difference in Days > 25◦C p.a. 41,910.000 -0.000 -0.111 7.427 -2.167 1.857Days > 30◦C p.a. 41,910.000 53.083 17.000 70.508 1.000 89.000Difference in Days > 30◦C p.a. 41,910.000 0.000 -0.176 19.719 -4.300 3.364Days > 90 Pctl p.a. 41,910.000 59.745 55.000 29.406 40.000 73.000Difference in Days > 90 Pctl p.a. 41,910.000 0.001 -2.429 23.308 -13.833 11.000Days > 95 Pctl p.a. 41,910.000 34.470 30.000 21.314 21.000 44.000Difference in Days > 95 Pctl p.a. 41,910.000 0.001 -2.323 17.489 -9.889 7.167Annual Average Temperature 41,910.000 22.054 24.966 7.407 14.653 28.474Operating Income (bef.depr.)/Assets (Year) 41,910.000 0.081 0.081 0.087 0.034 0.133Revenue/Assets (Year) 41,910.000 0.864 0.759 0.582 0.423 1.179Revenues mUSD (Year) 40,633.000 185.534 41.295 434.099 12.015 140.374Operating Income mUSD (Year) 40,912.000 29.162 3.960 90.247 0.578 15.835

Panel (B) Quarterly Data

(1) (2) (3) (4) (5) (6)VARIABLES N mean p50 sd p25 p75

Operating Income (bef.depr.)/Assets (Quarter) 150,077.000 0.020 0.020 0.029 0.006 0.036Revenue/Assets (Quarter) 150,077.000 0.229 0.194 0.167 0.107 0.308Total Assets mUSD 146,424.000 337.992 63.332 977.687 20.489 194.598Revenues mUSD (Quarter) 145,287.000 48.701 11.378 109.633 3.217 38.812Operating Income mUSD (Quarter) 147,350.000 8.112 1.011 26.311 0.095 4.322

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Additional TableLagged Quarterly Effect


Days > 25◦C p.q. -0.00174 -0.00186(0.0098) (0.0027)

Days > 30◦C p.q. -0.01511* -0.00194(0.0076) (0.0017)

Days > 90 Pctl p.q. -0.01403** -0.00243*(0.0059) (0.0014)

Days > 95 Pctl p.q. -0.01520** -0.00290(0.0072) (0.0019)

L.Days > 25◦C -0.00563 -0.00186(0.0079) (0.0019)

L.Days > 30◦C -0.02108*** -0.00467***(0.0075) (0.0015)

L.Days > 90 Pctl -0.01920*** -0.00316**(0.0064) (0.0013)

L.Days > 95 Pctl -0.01978** -0.00402**(0.0081) (0.0016)


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Additional TableLagged Annual Effect


Days > 25◦C p.q. -0.00174 -0.00186(0.0098) (0.0027)

Days > 30◦C p.q. -0.01511* -0.00194(0.0076) (0.0017)

Days > 90 Pctl p.q. -0.01403** -0.00243*(0.0059) (0.0014)

Days > 95 Pctl p.q. -0.01520** -0.00290(0.0072) (0.0019)

L.Days > 25◦C -0.00563 -0.00186(0.0079) (0.0019)

L.Days > 30◦C -0.02108*** -0.00467***(0.0075) (0.0015)

L.Days > 90 Pctl -0.01920*** -0.00316**(0.0064) (0.0013)

L.Days > 95 Pctl -0.01978** -0.00402**(0.0081) (0.0016)


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Additional TableLabor Intensity, Annual Effect


Days > 25◦C p.a. 0.07196 -0.00160(0.0472) (0.0050)

c.dy12#c.li2 -0.04124*** -0.00097(0.0041) (0.0008)

c.dy12#c.li3 -0.06424*** -0.00222(0.0050) (0.0015)

Days > 30◦C p.a. 0.01571 -0.00100(0.0166) (0.0036)

c.dy3012#c.li2 -0.07816*** -0.00201(0.0106) (0.0026)

c.dy3012#c.li3 -0.11211*** -0.00626(0.0134) (0.0043)

Days > 90 Pctl p.a. 0.06068*** 0.00217(0.0181) (0.0034)

c.dy90#c.li2 -0.12722*** -0.00439(0.0141) (0.0030)

c.dy90#c.li3 -0.19003*** -0.00634(0.0214) (0.0051)

Days > 95 Pctl p.a. 0.08757*** 0.00338(0.0236) (0.0045)

c.dy95#c.li2 -0.17375*** -0.00708(0.0234) (0.0045)

c.dy95#c.li3 -0.25299*** -0.00897(0.0350) (0.0069)


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Additional TableLabor Intensity, Quarterly Effect


Days > 25◦C p.a. 0.07196 -0.00160(0.0472) (0.0050)

c.dy12#c.li2 -0.04124*** -0.00097(0.0041) (0.0008)

c.dy12#c.li3 -0.06424*** -0.00222(0.0050) (0.0015)

Days > 30◦C p.a. 0.01571 -0.00100(0.0166) (0.0036)

c.dy3012#c.li2 -0.07816*** -0.00201(0.0106) (0.0026)

c.dy3012#c.li3 -0.11211*** -0.00626(0.0134) (0.0043)

Days > 90 Pctl p.a. 0.06068*** 0.00217(0.0181) (0.0034)

c.dy90#c.li2 -0.12722*** -0.00439(0.0141) (0.0030)

c.dy90#c.li3 -0.19003*** -0.00634(0.0214) (0.0051)

Days > 95 Pctl p.a. 0.08757*** 0.00338(0.0236) (0.0045)

c.dy95#c.li2 -0.17375*** -0.00708(0.0234) (0.0045)

c.dy95#c.li3 -0.25299*** -0.00897(0.0350) (0.0069)


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Additional TableRegional Distance Sales-Assets, Annual Effect


Days > 25◦C p.q. -0.00301 0.00020(0.0116) (0.0027)

Days > 30◦C p.q. -0.03449*** -0.00506**(0.0111) (0.0023)

Days > 90 Pctl p.q. -0.02482*** -0.00366**(0.0070) (0.0015)

Days > 95 Pctl p.q. -0.02981*** -0.00450**(0.0088) (0.0019)

c.dq12#c.Sales 0.00503 -0.00351(0.0144) (0.0035)

c.dq3012#c.Sales 0.01770* 0.00306(0.0092) (0.0023)

c.dq90#c.Sales 0.01016 0.00161(0.0073) (0.0019)

c.dq95#c.Sales 0.01677* 0.00220(0.0098) (0.0023)


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Additional TableRegional Distance Sales-Assets, Quarterly Effect


Days > 25◦C p.a. 0.01357 -0.00046(0.0372) (0.0059)

Days > 30◦C p.a. -0.04393 -0.00720**(0.0268) (0.0034)

Days > 90 Pctl p.a. -0.03986* -0.00386*(0.0195) (0.0022)

Days > 95 Pctl p.a. -0.04696** -0.00493*(0.0196) (0.0028)

c.dy12#c.Sales 0.00811 -0.00443(0.0474) (0.0079)

c.dy3012#c.Sales 0.01338 0.00612(0.0253) (0.0042)

c.dy90#c.Sales 0.00581 0.00355(0.0191) (0.0034)

c.dy95#c.Sales 0.01441 0.00491(0.0226) (0.0037)


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Additional TableLabor Intensity II, Quarterly


Days > 25◦C p.q. 0.02798*** -0.00013(0.0104) (0.0028)

c.dq12#c.ili2 -0.03249*** -0.00091(0.0031) (0.0006)

c.dq12#c.ili3 -0.03854*** -0.00217***(0.0037) (0.0007)

Days > 30◦C p.q. 0.00687 -0.00172(0.0087) (0.0019)

c.dq3012#c.ili2 -0.04585*** -0.00115(0.0065) (0.0013)

c.dq3012#c.ili3 -0.04536*** -0.00284*(0.0072) (0.0015)

Days > 90 Pctl p.q. 0.03617*** -0.00016(0.0108) (0.0021)

c.dq90#c.ili2 -0.06937*** -0.00187(0.0105) (0.0020)

c.dq90#c.ili3 -0.08027*** -0.00437**(0.0121) (0.0020)

Days > 95 Pctl p.q. 0.04517*** -0.00021(0.0147) (0.0029)

c.dq95#c.ili2 -0.08492*** -0.00290(0.0156) (0.0028)

c.dq95#c.ili3 -0.09405*** -0.00471*(0.0170) (0.0028)


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Additional TableLabor Intensity II, Annual


Days > 25◦C p.a. 0.04361 -0.00193(0.0406) (0.0050)

c.dy12#c.ili2 -0.03347*** -0.00076(0.0030) (0.0006)

c.dy12#c.ili3 -0.03564*** -0.00099(0.0033) (0.0008)

Days > 30◦C p.a. -0.00107 -0.00250(0.0157) (0.0034)

c.dy3012#c.ili2 -0.06180*** -0.00143(0.0086) (0.0017)

c.dy3012#c.ili3 -0.05412*** -0.00189(0.0077) (0.0021)

Days > 90 Pctl p.a. 0.03691** 0.00025(0.0171) (0.0031)

c.dy90#c.ili2 -0.10196*** -0.00259(0.0139) (0.0029)

c.dy90#c.ili3 -0.11521*** -0.00330(0.0146) (0.0028)

Days > 95 Pctl p.a. 0.06108** 0.00086(0.0221) (0.0040)

c.dy95#c.ili2 -0.14177*** -0.00458(0.0230) (0.0043)

c.dy95#c.ili3 -0.15419*** -0.00423(0.0244) (0.0043)


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Additional TableGDP Quintiles, Quarterly


Days > 25◦C p.q. -0.00574 -0.00325(0.0231) (0.0049)

Days > 30◦C p.q. -0.02608 -0.00532(0.0204) (0.0043)

Days > 90 Pctl p.q. -0.04669*** -0.00947***(0.0142) (0.0027)

Days > 95 Pctl p.q. -0.05497*** -0.01177***(0.0191) (0.0038)

c.dq12#c.gdp5 0.00283 0.00060(0.0088) (0.0018)

c.dq3012#c.gdp5 0.00180 0.00113(0.0099) (0.0020)

c.dq90#c.gdp5 0.01230** 0.00275***(0.0049) (0.0008)

c.dq95#c.gdp5 0.01560** 0.00350***(0.0068) (0.0011)


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Additional TableGDP Quintiles, Annual


Days > 25◦C p.a. -0.03143 -0.01174(0.0434) (0.0077)

Days > 30◦C p.a. -0.03521 -0.00550(0.0540) (0.0092)

Days > 90 Pctl p.a. -0.09825*** -0.01522***(0.0333) (0.0051)

Days > 95 Pctl p.a. -0.10933** -0.01937***(0.0396) (0.0059)

c.dy12#c.gdp5 0.00965 0.00240(0.0202) (0.0029)

c.dy3012#c.gdp5 -0.00311 0.00060(0.0240) (0.0048)

c.dy90#c.gdp5 0.02622* 0.00525***(0.0130) (0.0017)

c.dy95#c.gdp5 0.03184* 0.00700***(0.0176) (0.0021)


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Additional TableTemperature Quintiles, Quarterly


Days > 25◦C p.q. 0.02734 0.00426(0.0217) (0.0054)

Days > 30◦C p.q. 0.01984 0.01070*(0.0343) (0.0059)

Days > 90 Pctl p.q. 0.01344 0.00402*(0.0109) (0.0022)

Days > 95 Pctl p.q. 0.01272 0.00507*(0.0147) (0.0028)

c.dq12#c.temp5 -0.00845 -0.00197(0.0060) (0.0015)

c.dq3012#c.temp5 -0.00964 -0.00318**(0.0079) (0.0014)

c.dq90#c.temp5 -0.00938*** -0.00211***(0.0033) (0.0007)

c.dq95#c.temp5 -0.00932** -0.00259***(0.0043) (0.0009)


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Additional TableTemperature Quintiles, Annual


Days > 25◦C p.a. 0.00364 -0.00515(0.0766) (0.0125)

Days > 30◦C p.a. -0.00267 0.00215(0.0853) (0.0172)

Days > 90 Pctl p.a. 0.01828 0.00388(0.0367) (0.0047)

Days > 95 Pctl p.a. 0.01354 0.00498(0.0495) (0.0059)

c.dy12#c.temp5 -0.00249 -0.00004(0.0171) (0.0032)

c.dy3012#c.temp5 -0.00841 -0.00150(0.0214) (0.0035)

c.dy90#c.temp5 -0.01627 -0.00201(0.0109) (0.0017)

c.dy95#c.temp5 -0.01433 -0.00239(0.0132) (0.0017)


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Additional TableCost Margin

(1) (2) (3) (4) (5) (6) (7) (8)VARIABLES XOP-R XOP-R XOP-R XOP-R XOP-R XOP-R XOP-R XOP-R

Days > 25◦C p.q. 0.03568(0.0244)

Days > 30◦C p.q. 0.00876(0.0160)

Days > 90 Pctl p.q. 0.02671**(0.0125)

Days > 95 Pctl p.q. 0.02917*(0.0165)

Days > 25◦C p.a. 0.01999(0.0190)

Days > 30◦C p.a. -0.00835(0.0079)

Days > 90 Pctl p.a. -0.00070(0.0075)

Days > 95 Pctl p.a. -0.00357(0.0091)


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Additional TablePlausibility Check (Geography), Quarterly

(1) (2) (3) (4) (5) (6)VARIABLES Rev-Assets Rev-Assets Rev-Assets OpInc-Assets OpInc-Assets OpInc-Assets

Days > 25◦C p.q. 0.00317 -0.00193(0.0096) (0.0027)

Days > 90 Pctl p.q. -0.02031*** -0.00391***(0.0055) (0.0014)

Days > 95 Pctl p.q. -0.02176*** -0.00472**(0.0071) (0.0019)

c.dq12#c.scandinavia -0.09957 0.01222(0.0902) (0.0146)

c.dq90#c.scandinavia 0.03650* 0.01757***(0.0209) (0.0039)

c.dq95#c.scandinavia 0.05096 0.02549***(0.0324) (0.0055)

Observations 150,077 150,077 150,077 150,077 150,077 150,077R-squared 0.830 0.830 0.830 0.559 0.560 0.560Number Firms 4410 4410 4410 4410 4410 4410

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Additional TablePlausibility Check (Geography), Annual

(1) (2) (3) (4) (5) (6)VARIABLES Rev-Assets Rev-Assets Rev-Assets OpInc-Assets OpInc-Assets OpInc-Assets

Days > 25◦C p.a. 0.03605 -0.00331(0.0318) (0.0052)

Days > 90 Pctl p.a. -0.03218** -0.00340(0.0116) (0.0027)

Days > 95 Pctl p.a. -0.03298*** -0.00395(0.0116) (0.0031)

c.dy12#c.scandinavia -0.42470 -0.00727(0.2589) (0.0446)

c.dy90#c.scandinavia 0.01299 0.02848***(0.0394) (0.0082)

c.dy95#c.scandinavia 0.00532 0.03530***(0.0548) (0.0119)

Observations 41,910 41,910 41,910 41,910 41,910 41,910R-squared 0.829 0.829 0.829 0.600 0.600 0.600Number Firms 4410 4410 4410 4410 4410 4410

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IPCC 1.5◦Report

B. Projected Climate Change, Potential Impacts and Associated RisksB1. Climate models project robust differences in regional climate characteristics betweenpresent-day and global warming of 1.5◦C, and between 1.5◦C and 2◦C. These differencesinclude increases in: mean temperature in most land and ocean regions (highconfidence), hot extremes in most inhabited regions (high confidence), heavyprecipitation in several regions (medium confidence), and the probability of drought andprecipitation deficits in some regions (medium confidence).Source: Global Warming of 1.5◦C an IPCC special report on the impacts of globalwarming of 1.5 ◦C above pre-industrial levels and related global greenhouse gas emissionpathways, in the context of strengthening the global response to the threat of climatechange, sustainable development, and efforts to eradicate povertyhttp://report.ipcc.ch/sr15/pdf/sr15_headline_statements.pdf


http://report.ipcc.ch/sr15/pdf/sr15_headline_statements.pdf

FAQ

Why should I care?

1st because the increases in risk would suggest that there is a strong financialincentive to change behavior.

2nd because neglecting impact problematic for institutions and because verydifferent approach currently pursued.

3rd if you are environmental economist, need for cooling.

What is H0?

1st that firms adapt or are insensitive, or that the effect is net zero

2nd that analysts anticipate impact.

Why do firms behave like that?

Now even rational to do what they do.

Investors - attention.

What now?

Supply chains

Trends


Literature Questions

Total econ effect:

Burke, Hsiang, Miguel (2015) peak at 13◦C, strongly declining at ET, holds since1960, both agri/nonagri, rich and poor, natural capital not subsitutable

Projections:

Not just agriculture: DJO (2012) AER, Burke et al. (2015), Hsiang (2010) thatnonagricultural losses are larger.

Labor component: Hsiang (2010) response is structurally similar; Graff Zivin andNeidell (2014): reduction in hours worked; Deryugina and Hsiang (2014): reductionincome US

Airco: Niemela et al. () for call center study

Other finance:

Other econ:

Cold: DJO (2012) symmetric impact, but reduction due to inhabited area effect,mortality impact, but general projection that this will not be offset, Pilcher (2002)both hot and cold have an impact

Other temperatures: Sepannen (2003): no effect zone


Country and industry composition

africa 5,200 2%

asean 80,800 34%

eastasia 39,700 17%

middle east 14,400 6%

northern europe 13,400 6%

south asia 8,790 4%

southern europe 11,970 5%

western europe 35,400 14%


Documents

Climate Change, Firm Performance & Investor Surprises€¦ · Task Force Climate-Related Financial Disclosure: Climate change \one of the most signi cant, and perhaps most misunderstood,