The Effect of Climate Change on Canadian Farmland Values: A Ricardian Approach

Nicholas Bannon; Christopher Kimmerer; B. James Deaton

doi:10.3368/le.101.2.022624-0017R1

Article Figures & Data

Tables

Additional Files

View popup

Table 1

Statistics for Farmland Sales Data

	2017	2018	2019	2020	2021	2022	Total
Mean
Total (Can$)	578,900	507,687	425,418	457,303	517,767	582,647	507,874
Price/acre (Can$)	10,836	8,920	8,142	9,743	11,671	11,300	10,176
Acres	153	117	96	95	98	99	106
SD
Total (Can$)	860,079	693,685	601,353	639,455	882,670	977,641	793,251
Price/acre (Can$)	37,839	24,482	25,101	31,319	37,239	41,941	33,872
Acres	251	144	102	75	106	71	128
Median
Total (Can$)	347,700	290,000	243,861	263,755	275,000	322,000	286,000
Price/acre (Can$)	2,924	2,747	2,500	2,758	2,800	3,118	2,807
Acres	100	97	95	94	95	95	95
Observations	5,097	6,297	7,860	8,294	10,034	8,124	45,706

View popup

Table 2

Historical and Predicted Climate Data Statistics

	Mean	SD	Median
Historical precipitation (mm)
January	39.8	35.8	21.4
April	45.0	27.3	29.2
July	74.5	19.2	76.0
October	49.2	35.7	32.2
Historical temperature (°C)
January	−11.2	4.8	−12.2
April	4.6	1.7	4.2
July	18.5	1.6	18.5
October	5.7	2.5	4.9
Future precipitation (mm)
January	43.6	36.0	25.0
April	46.7	26.8	33.0
July	72.1	20.2	72.0
October	44.1	32.1	30.0
Future temperature (°C)
January	−9.9	5.1	−11.1
April	6.8	1.8	6.3
July	21.2	1.7	21.4
October	9.0	2.0	8.5

Note: Future climate variables are based on the SSP2-4.5 scenario for 2041–2070.

View popup
Table 3
Statistics for Selected Control Variables
Mean SD Median
Census subdivision median income (Can$) 37,437 6,312 37,675
Census subdivision population density (pop/km²) 31.6 137.1 1.6
Proximity variable (km) 178 155 135
Note: The proximity variable measures the distance by road to the nearest population center with a population of 90,000 or more.

View popup

Table 4

Selected Coefficient Estimates

	Census Division Fixed Effects		Provincial Fixed Effects		Base
	(1)	(2)	(3)	(4)	(5)	(6)
Temperature (°C)
January	25.678^***	30.160^***	47.401^***	36.551^***	30.999^***	23.449^***
(1.933)	(1.898)	(1.218)	(1.213)	(1.154)	(1.177)
January squared	1.253^***	1.466^***	1.989^***	1.571^***	1.442^***	1.151^***
January squared	(0.076)	(0.076)	(0.051)	(0.050)	(0.051)	(0.053)
April	23.415^***	24.171^***	16.225^***	11.484^***	11.099^***	7.277^***
April	(3.622)	(3.558)	(2.198)	(2.150)	(2.062)	(2.092)
April squared	0.845^*	0.458	0.685^**	1.353^***	1.837^***	2.359^***
April squared	(0.338)	(0.332)	(0.229)	(0.224)	(0.210)	(0.209)
July	−75.489^***	−74.964^***	−129.814^***	−118.521^***	−112.564^***	−117.735^***
July	(11.626)	(11.214)	(8.496)	(8.208)	(8.212)	(8.090)
July squared	1.916^***	2.083^***	3.722^***	3.364^***	2.782^***	2.854^***
July squared	(0.325)	(0.313)	(0.245)	(0.237)	(0.240)	(0.235)
October	29.544^***	16.803^***	78.684^***	45.820^***	96.737^***	75.814^***
October	(3.470)	(3.445)	(2.499)	(2.563)	(2.570)	(2.627)
October squared	−3.032^***	−2.440^***	−6.831^***	−4.826^***	−6.650^***	−5.334^***
October squared	(0.276)	(0.271)	(0.166)	(0.170)	(0.167)	(0.172)
Precipitation (mm)
January	0.655^**	0.521^**	2.522^***	2.279^***	2.257^***	2.110^***
January	(0.207)	(0.197)	(0.144)	(0.136)	(0.120)	(0.120)
January squared	−0.002	−0.001	−0.011^***	−0.010^***	−0.009^***	−0.008^***
January squared	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)
April	2.307^***	2.254^***	0.937^***	0.834^***	2.755^***	2.036^***
April	(0.264)	(0.261)	(0.202)	(0.206)	(0.197)	(0.205)
April squared	−0.009^***	−0.009^***	0.000	−0.000	−0.005^**	−0.003
April squared	(0.002)	(0.002)	(0.002)	(0.002)	(0.002)	(0.002)
July	3.231^***	1.742^***	3.978^***	2.235^***	2.672^***	1.451^***
July	(0.320)	(0.320)	(0.163)	(0.168)	(0.157)	(0.165)
July squared	−0.020^***	−0.012^***	−0.018^***	−0.013^***	−0.006^***	−0.003^**
July squared	(0.002)	(0.002)	(0.001)	(0.001)	(0.001)	(0.001)
October	−1.491^***	−0.749^**	−3.074^***	−1.985^***	−3.039^***	−1.824^***
October	(0.249)	(0.247)	(0.169)	(0.167)	(0.154)	(0.159)
October squared	0.002	-0.000	0.011^***	0.008^***	0.005^***	0.002
October squared	(0.002)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)
Distance (km)
Distance		−0.283^***		−0.214^***		−0.183^***
Distance		(0.011)		(0.006)		(0.006)
Census subdivision controls	Yes	Yes	Yes	Yes	Yes	Yes
Soil quality controls	Yes	Yes	Yes	Yes	Yes	Yes
Census division fixed effects	Yes	Yes
Provincial fixed effects			Yes	Yes
Year fixed effects	Yes	Yes	Yes	Yes	Yes	Yes
Observations	45,552	45,552	45,706	45,706	45,706	45,706
R-squared	0.803	0.807	0.732	0.742	0.714	0.722

Note: Coefficients and standard errors are multiplied by 100. Robust standard errors are in parentheses. Models 1 and 2 omit census divisions with less than 10 observations. The coefficient estimates (× 100) of the squared distance variables in columns (2), (4), and (6) are 0.000130, 0.000118, and 0.000107, respectively, and all are significant at the 99.99% level.
↵^* p < 0.05; ^** p < 0.01; ^*** p < 0.001.

View popup

Table 5

Marginal Impacts of Climate on Farmland Values

	Census Division Fixed Effects				Provincial Fixed Effects				Base
	(1)		(2)		(3)		(4)		(5)		(6)
Temperature (°C)
January	−2.46	(0.74)	−2.76	(0.72)	2.75	(0.50)	1.28	(0.49)	−1.38	(0.51)	−2.40	(0.52)
April	31.11	(2.07)	28.34	(2.07)	22.46	(1.27)	23.80	(1.22)	27.82	(1.07)	28.75	(1.08)
July	−4.53	(2.07)	2.15	(2.07)	8.00	(1.44)	6.02	(1.40)	−9.53	(1.39)	−12.07	(1.40)
October	−5.29	(1.86)	−11.22	(1.86)	0.15	(1.50)	−9.66	(1.48)	20.29	(1.37)	14.50	(1.36)
Aggregate (%)	18.83		16.51		33.36		21.44		37.20		28.78
Precipitation (mm)
January	0.52	(0.16)	0.47	(0.16)	1.64	(0.09)	1.47	(0.09)	1.56	(0.08)	1.44	(0.08)
April	1.52	(0.14)	1.45	(0.13)	0.95	(0.10)	0.79	(0.10)	2.29	(0.09)	1.80	(0.09)
July	0.27	(0.07)	−0.01	(0.07)	1.25	(0.04)	0.30	(0.05)	1.71	(0.04)	0.97	(0.04)
October	−1.33	(0.15)	−0.78	(0.15)	−1.95	(0.10)	−1.18	(0.1)	−2.52	(0.09)	−1.66	(0.10)
Aggregate (%)	0.98		1.13		1.89		1.38		3.04		2.55
Proximity variable			Yes				Yes				Yes

Note: Marginal impacts represent the percentage change in land values attributed to a one-unit change in a specific climate variable (ceteris paribus). All marginal impacts are calculated at the mean historical climate conditions. Standard errors are in parentheses.

View popup

Table 6

Average Ricardian Impacts under the SSP2.4-5 2041–2070 Climate Scenario ($/Acre)

	Census Division Fixed Effects		Provincial Fixed Effects		Base
	(1)	(2)	(3)	(4)	(5)	(6)
Per-acre price (Can$)	9,532	9,532	9,526	9,526	9,526	9,526
Predicted per-acre price (%)	9,884	9,906	10,016	9,997	10,255	10,306
95% confidence interval (Can$)	(9,627, 10,142)	(9,646, 10,166)	(9,725, 10,307)	(9,711, 10,283)	(9,945, 10,565)	(9,993, 10,620)
Predicted future price (Can$)	15,160	15,607	13,039	13,538	17,413	17,843
95% confidence interval (Can$)	(14,851, 15,469)	(15,283, 15,931)	(12,840, 13,238)	(13,282, 13,793)	(17,124, 17,703)	(17,490, 18,197)
Per-acre change (2041–2070) (Can$)	5,276	5,701	3,023	3,541	7,159	7,537
Annualized impacts (5%) (Can$)	264	285	151	177	358	377
% change	53	58	30	35	70	73
Proximity variable		Yes		Yes		Yes

Note: Impacts are in 2017 Canadian dollars (Statistics Canada 2023c), and 95% confidence intervals from 1,000 bootstrap replications are in parentheses. All models include census subdivision and soil controls; only pooled models include year fixed effects. Models 1 and 2 omit observations in census divisions with fewer than 10 observations.

View popup

Table 7

Ricardian Impacts by Province under the SSP2.4-5 2041–2070 Climate Scenario ($/Acre)

	British Columbia	Alberta	Saskatchewan	Manitoba	Ontario	Quebec	New Brunswick	Novia Scotia	Total
Per-acre price (Can$)	62,625	3,527	1,704	2,521	13,393	8,510	3,245	4,168	9,532
Predicted per-acre price (Can$)	64,550	3,656	1,729	2,435	14,247	9,206	2,922	3,958	9,906
Predicted future price (Can$)	78,395	4,341	2,361	3,728	32,377	20,711	6,147	8,240	15,607
Per- acre change (Can$)	13,845	685	632	1,293	18,130	11,505	3,225	4,281	5,701
Annualized impacts (5%) (Can$)	692	34	32	65	906	575	161	214	285
% change	21	19	37	53	127	125	110	108	58
Observations	3,549	9,789	14,400	5,044	7,556	4,096	588	530	45,552

Note: Land values have been adjusted for inflation and impacts are in 2017 Canadian dollars (Statistics Canada 2023c). Minimum 10 observations per county are required to be included; all models are pooled cross sections and include year and county fixed effects and the proximity variable.

View popup

Table 8

Average Percentage Change of Per-Acre Farmland Values across Various Ricardian Models

Model	Log-Quadratic: Cultivated Fruit and Pastureland Use	Log-Linear: Cultivated Fruit and Pastureland Use	Weighted Least Squares: Cultivated Fruit and Pastureland Use	Log-Quadratic: All Land Uses
(1)	(2)	(3)	(4)	(5)
Census division fixed effects	53	55	46	67
Census division fixed effects (proximity)	58	43	59	74
Provincial fixed effects	30	120	16	57
Provincial fixed effects (proximity)	35	73	27	68
Base	70	125	32	65
Base (proximity)	73	94	36	75

Note: The weighted least squares model weights each parcel based on the percentage of total acres. The percentage change measures the percentage difference between predicted future and predicted historical prices. All models are pooled cross sections and use the climate scenario SSP2-4.5 for 2041–2070. The log-linear and weighted least squares model restrict the sample to cultivated fruit and pastureland uses.