Supply Chain Climate Exposure

Figures & data

Figure 1. A Simplified Comparison between Scope 3 Emissions and Downstream Supply Chain Climate Exposure

Note: The schematic shows which data inputs are relevant for each climate measure, highlighting the product-centric nature of scope 3 emissions and the economic linkage-centric nature of the downstream supply chain climate exposure measure proposed in this paper. Source: AQR. For illustrative purposes only.

Table 1. Computing Downstream Supply Chain Climate Exposure for a Hypothetical Company, i, with Four Customers, j = A, B, C, and D

	Customer’s Carbon Intensity		Imputed % Revenue
	$\left(C_j\right)$	% Revenue from Each Customer	$\left(w_{ij}\right)$
Customer A	200	40%	40%
Customer B	100	30%	30%
Customer C	100	NA	15%
Customer D	50	NA	15%

Source: AQR. For illustrative purposes only.

Figure 2. Carbon Emissions Statistics over Time

Note: The downstream supply chain climate exposure and scope 1, scope 2, and scope 3 emissions intensity for the median MSCI World constituent in Panel A and for the overall MSCI World Index in Panel B for the period of June 2009 to December 2021. Source: AQR, MSCI, Trucost.

Figure 3. Sector- and Country-Level Contributions to MSCI World Index–Level Carbon Emissions Metrics

Note: Each sample quarter, percentage contributions to MSCI World Index are calculated from each sector (Panel A) and each country or broader region (Panel B) as of December 31, 2021. The charts show the time series averages of these contributions. In Panel A, the historically deprecated Telecommunication is omitted from the chart. Source: AQR, Trucost, MSCI.

Table 2. Explaining Downstream Supply Chain Carbon Exposure with Traditional Climate Data

	(1)	(2)	(3)	(4)
ln CO2 intensity, scope 1	0.29**			0.08**
	(56.08)			(14.43)
ln CO2 intensity, scope 2	−0.09**			0.01
	(−8.63)			(1.76)
ln CO2 intensity, scope 3	0.15**			0.09**
	(13.03)			(6.83)
MSCI E-pillar score		−0.05**		0.00
		(−4.16)		(0.90)
MSCI climate change score			−0.04**	0.02**
			(−5.40)	(3.93)
Sector + region indicator	NO	NO	NO	YES
Observations	77,194	84,249	65,727	55,970
R^2	0.280	0.011	0.010	0.461
Number of x-sections	51	51	36	36

Note: Estimates are from Fama-MacBeth regressions of the downstream supply chain carbon exposure (in logs) on scope 1, 2, 3 carbon intensity (in logs), MSCI E-pillar, and MSCI Climate Change theme. Regressions (1)–(3) do not include any additional explanatory variables; regression (4) also includes sector and regional indicator variables. The regressions are run quarterly from June 2009 to December 2021 for the developed large-cap universe (MSCI World); the table presents time series estimates t-statistics adjusted for heteroskedasticity and auto-correlation with Newey-West procedure with 4 lags.

*Indicates significance on a 5% basis and **Indicates significance on a 1% basis.

Source: AQR, Trucost, MSCI.

Figure 4. Correlation of Market-Wide Climate Sentiment with Factors Built Using Downstream Supply Chain Carbon Exposure

Note: The top panel shows monthly return correlations with the monthly changes in climate news sentiment index of Ardia et al. (2021) for factors based on downstream supply chain climate exposure overall and within-industry exposure as well as after removing the commonality with other typical climate-related data. The bottom panel shows similar correlations for a hypothetical long-short portfolio based on typical climate-related data, removing the commonality with the downstream supply chain measure, as indicated in the chart. The hypothetical portfolio ranks stocks on (negated) downstream supply chain carbon exposure; neutralizes country and, as indicated, industry exposures; removes market exposures based on ex-ante beta; and targets 7% ex ante volatility. This hypothetical portfolio is rebalanced monthly. Returns are gross of transaction costs, financing costs, and fees. Given the available climate sentiment data, the sample period is June 2009 through June 2018. Hypothetical performance results have many inherent limitations, some but not all of which are described herein. No representation is being made that any fund or account will or is likely to achieve profits or losses similar to those shown herein. Hypothetical performance results are presented for illustrative purposes only. Hypothetical performance is gross of advisory fees and transaction costs and includes the reinvestment of dividends. If the expenses were reflected, the performance shown would be lower.

Figure 5. Stock Reaction to Climate News Events

Note: Daily cumulative beta-adjusted returns to the longs and shorts from the downstream supply chain climate exposure factor, in the 30-day window surrounding two climate events: G8 committing to reducing emissions by 80% by 2050 on 9th July 2009 (Panel A) and President Trump withdrawing the U.S. from the Paris Agreement on 1st June 2017 (Panel B). The long and short side are beta-adjusted using the MSCI World Index benchmark. Universe of large-cap developed markets stocks, similar to MSCI World Index constituents. The long-short factor portfolio ranks stocks on their (negated) supply chain carbon exposure, neutralizes country and industry exposures, removes market exposures based on ex ante beta, and targets 7% ex ante volatility. This hypothetical portfolio is rebalanced monthly. Returns are gross of transaction costs, financing costs, and fees. Source: AQR.

Table 3. Portfolio Performance for Longshort Portfolios Based on Downstream Supply Chain Climate Exposure

	Unadjusted	Within-Industry
Average return	7.4%	6.5%
Standard deviation of returns	8.7%	9.0%
Sharpe ratio	0.85	0.72
Beta to MSCI World	−0.07	−0.05
Hit ratio	56%	56%

Note: Universe of large-cap developed markets stocks, similar to MSCI World constituents. The long-short portfolio ranks stocks on (negated) downstream supply chain carbon exposure, neutralizes country and, when indicated, industry exposures, and removes ex-ante market exposures and targets 7% ex ante volatility. This hypothetical portfolio is rebalanced monthly. Returns are gross of transaction costs, financing costs, and fees. The sample period is June 2009 to December 2021.

Source: AQR.

Table 4. Factor-Adjusted Performance of Downstream Supply Chain Climate Exposure (DSChCE) Long-Short Portfolios

	Unadjusted DSChCE Portfolio			Within-Industry DSChCE Portfolio			Within-Industry DSChCE Portfolio
	Unadjusted Academic Factors			Unadjusted Academic Factors			Within-Industry Academic Factors
	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
Alpha	6.48%**	9.41%**	8.92%**	5.31%*	4.95%	6.55%*	5.98%*	4.85%*	3.80%
	(2.70)	(3.92)	(3.41)	(2.15)	(1.91)	(2.35)	(2.45)	(1.97)	(1.46)
Mkt-rf	−0.02	−0.05	−0.05	−0.01	0.01	0.02	−0.02	−0.03	−0.03
	(−0.52)	(−1.12)	(−1.03)	(−0.22)	(0.16)	(0.31)	(−0.35)	(−0.52)	(−0.59)
Size	−0.05	−0.23	−0.25*	0.17	0.19	0.26	−0.19*	−0.21*	−0.21*
	(−0.38)	(−1.71)	(−1.75)	(1.26)	(1.32)	(1.75)	(−2.24)	(−2.52)	(−2.40)
Value	−0.39**	−0.56**	−0.53**	−0.44**	−0.57**	−0.51**	−0.40**	−0.27**	−0.18
	(−4.58)	(−4.34)	(−3.56)	(−4.99)	(−4.08)	(−3.17)	(−5.13)	(−3.03)	(−1.24)
Profitability		−0.73**	−0.75**		−0.01	0.05		0.18*	0.17*
		(−4.10)	(−4.08)		(−0.04)	(0.26)		(2.24)	(2.19)
Conservatism		−0.02	−0.05		0.31	0.33		−0.14*	−0.15*
		(−0.10)	(−0.23)		(1.34)	(1.37)		(−2.06)	(−2.15)
Momentum			0.02			0.13			0.07
			(0.24)			(1.27)			(0.44)
BAB			0.04			−0.23			0.11
			(0.36)			(−1.88)			(1.19)
Observations	151	151	151	151	151	151	151	151	151
R^2	0.142	0.233	0.235	0.151	0.162	0.184	0.160	0.208	0.217

Note: Monthly returns of the downstream supply chain climate exposure long-short portfolio are regressed on the factors indicated in row labels. Regressions (1)–(3) use the portfolio defined both across- and within-industry; in (4)–(9), the portfolio is based on within-industry supply chain exposures only. Regressions (1)–(6) use academic factors (Market, Size, Value, Profitability, Conservatism, and Momentum are Mkt-rf, SMB, HML, RMW, CMA, and UMD, respectively from Ken French’s Data Library; BAB is from the AQR Data Library), and regressions (7)–(9) use the within-industry versions of those factors, defined using equivalent stock characteristics (e.g., market cap for Size, book-to-price for Value, etc.). Alphas are annualized, and t-statistics are shown in parentheses. The sample period is June 2009 to December 2021.

* indicates significance on a 5% basis and ** indicates significance on a 1% basis.

Source: AQR, Ken French’s Data Library.

Table 5. Regressions Relating Quarterly EPS and Sales Surprises to Downstream Supply Chain Climate Exposure

	Unadjusted		Industry Demeaned
Additional Controls	EPS	Sales	EPS	Sales
No additional controls	9.30**	5.64**	3.83**	1.72
Analyst revisions	7.77**	5.02**	3.04**	0.79
Analyst revisions + Profitability + ΔProfitability + Momentum	9.24**	5.55**	3.38**	1.03

Note: Each quarter, EPS and Sales surprises, as indicated in column headers, are regressed on a given firm’s downstream supply chain climate exposure and additional controls prior to the earnings announcement, as indicated by row labels. The table shows the t-statistics of the coefficient on supply chain climate exposure, obtained from the time series of cross-sectional regressions using the Fama-MacBeth method. The t-statistics are adjusted for heteroskedasticity and auto-correlation with Newey-West procedure with four lags. Profitability is defined as return on net operating assets; Fundamental Momentum is defined as 1-year change in Profitability; and Price Momentum is based on the total return of stocks in the past 12 months excluding the most recent month. The data in the right panel is industry-demeaned. The sample period is June 2009 to December 2021. Universe is large-cap developed markets stocks, similar to MSCI World constituents.

*Indicates significance on a 5% basis and ** Indicates significance on a 1% basis.

Source: AQR.

Ardia, David, Keven Bluteau, Kris Boudt, and Koen Inghelbrecht. 2021. Climate Change Concerns and the Performance of Green versus Brown Stocks, working paper, National Bank of Belgium.

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