Impact of regional agriculture on economic development: A reflection from Lincolnshire, the United Kingdom

doi:10.1016/j.regsus.2026.100353

Abstract

Abstract:

Agriculture is a crucial pillar for economic growth, food security, and trade, therefore, it is necessary to study how the performance of agriculture affects the overall situation of a country. This study assessed the extent to which agricultural production in Lincolnshire shapes the agricultural performance of the United Kingdom (UK) and contributes to the economic development of the country. This study used the Chow test and parsimonious vector autoregressive (VAR) model to analyze data (Gross Value Added (GVA) for agriculture in Lincolnshire during 1997-2023, and GVA for agriculture in the UK, gross domestic product (GDP) in the UK, and agricultural trade balance (ATB) in the UK during 1990-2023) sourced from the Food and Agriculture Organization Statistics (FAOSTAT), Office of National Statistics, Statistica, and the UK Government. The results indicated that GVA for agriculture in Lincolnshire accounted for 4.30%-6.90% of the national GVA for agriculture during 1997-2023, and it increased by 57.20% during the study period. Structural break analysis revealed statistically significant breaks of GVA for agriculture in Lincolnshire at 5%, 10%, and 1% significance levels in 2004, 2008, and 2013, respectively. The current level of GVA for agriculture in Lincolnshire was negatively influenced by the GDP level of previous two years and positively influenced by the ATB level of previous one year. In conclusion, GVA for agriculture in Lincolnshire was strongly endogenous, whereas GDP and ATB were weakly exogenous with respect to GVA for agriculture. Furthermore, GVA for agriculture, GDP, and ATB in the UK exerted asymmetric effects on GVA for agriculture in Lincolnshire. This study recommends leveraging the governance opportunities presented by devolution to provide sustained support for agricultural production through mechanisms analogous to the Common Agricultural Policy, particularly in relation to subsidy provision. Devolution can further promote local consumption through targeted campaigns and may serve as a foundation for developing Lincolnshire-specific policies that can strengthen agricultural production and export.

Key words: Agricultural trade balance (ATB), Gross domestic product (GDP), Gross Value Added (GVA) for agriculture, Parsimonious vector autoregressive (VAR) model, Lincolnshire, The United Kingdom (UK)

Saul NGARAVA. Impact of regional agriculture on economic development: A reflection from Lincolnshire, the United Kingdom[J]. Regional Sustainability, 2026, 7(3): 100353.

Figures/Tables 10

Table 1

Fig. 1.

Fig. 2.

Table 2

Table 3

Table 4

Vector Autoregressive (VAR) model results for different variables."

	General VAR model				Parsimonious VAR model
	d(lnGVA_{UK per capita})	d(lnGVA_{L per capita})	d(lnGDP_{UK per capita})	d(lnATB_{UK per capita})	d(lnGVA_{UK per capita})	d(lnGVA_{L per capita})	d(lnGDP_{UK per capita})	d(lnATB_{UK per capita})
d(lnGVA_{UK per capita} (-1))	-0.577^** (0.241) [-2.400]	-0.026 (0.225) [-0.116]	-0.074 (0.054) [-1.367]	-0.109 (0.219) [-0.498]	-0.573^*** (0.208) [-2.751]	-	-0.061 (0.049) [-1.227]	-
d(lnGVA_{UK per capita} (-2))	-0.425^* (0.245) [-1.737]	0.191 (0.229) [0.834]	0.044 (0.055) [0.796]	-0.108 (0.222) [-0.485]	-0.435^** (0.217) [-1.998]	0.187 (0.189) [0.990]	0.045 (0.051) [0.890]	-
d(lnGVA_{L per capita} (-1))	-0.033 (0.270) [-0.124]	-0.156 (0.253) [-0.616]	-0.068 (0.061) [-1.117]	-0.068 (0.246) [-0.278]	-	-0.153 (0.232) [-0.662]	-0.061 (0.058) [-1.064]	-
d(lnGVA_{L per capita} (-2))	-0.119 (0.233) [-0.509]	0.047 (0.218) [0.215]	0.021 (0.052) [0.407]	-0.134 (0.212) [-0.633]	-0.134 (0.210) [-0.637]	-	-	-0.125 (0.178) [-0.705]
d(lnGDP_{UK per capita} (-1))	0.652 (1.106) [0.589]	-1.114 (1.035) [-1.075]	0.321 (0.248) [1.298]	1.501 (1.005) [1.494]	0.623 (1.082) [0.576]	-1.202 (0.944) [-1.274]	0.313 (0.233) [1.340]	1.549^* (0.797) [1.943]
d(lnGDP_{UK per capita} (-2))	0.411 (1.524) [0.270]	-2.501^* (1.427) [-1.753]	-0.374 (0.341) [-1.098]	0.265 (1.385) [0.192]	-	-2.474^** (1.214) [-2.039]	-0.355 (0.314) [-1.130]	-
d(lnATB_{UK per capita} (-1))	0.102 (0.287) [0.357]	0.458^* (0.268) [1.706]	0.077 (0.064) [1.198]	-0.538^** (0.261) [-2.065]	-	0.447^* (0.245) [1.825]	0.077 (0.061) [1.262]	-0.512^** (0.207) [-2.476]
d(lnATB_{UK per capita} (-2))	0.095 (0.270) [0.352]	0.167 (0.252) [0.662]	0.082 (0.060) [1.362]	-0.170 (0.245) [-0.695]	-	0.209 (0.218) [0.960]	0.064 (0.054) [1.185]	-0.195 (0.214) [-0.915]
Constant	-0.034 (0.062) [-0.547]	0.111^* (0.058) [1.918]	0.027^* (0.014) [1.940]	0.048 (0.056) [0.853]	-0.027 (0.050) [-0.528]	0.109^** (0.053) [2.068]	0.029^** (0.013) [2.174]	0.051 (0.042) [1.212]
R²	0.379	0.376	0.321	0.393	0.371	0.373	0.290	0.377
Adjusted R²	0.047	0.043	-0.042	0.069	0.197	0.164	-0.003	0.246
Durbin Watson statistic	1.684	2.160	2.086	1.552	1.730	2.070	2.070	1.593
Log(likelihood)	117.675
AIC	-6.806
SIC	-5.039

Table 4

Table 5

Fig. 3.

Fig. 4.

Table S1

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	GVA for agriculture in the United Kingdom (UK)	GVA for agriculture in Lincolnshire	GDP in the UK	ATB in the UK
Mean (×10⁹ GBP)	11.18	0.57	1490.01	-15.30
Standard deviation (×10⁹ GBP)	2.15	0.20	563.13	8.66
Kurtosis	-0.60	1.09	-0.81	-0.15
Skewness	-0.19	1.15	0.32	-0.65
Minimum (×10⁹ GBP)	7.41	0.32	670.80	-37.34
Maximum (×10⁹ GBP)	15.91	1.10	2717.32	-5.02
t-statistic	30.35	14.90	15.43	-10.30
Number of observations	34	27	34	34

Year	Statistic	Statistical value	P-value
2004	F-statistic	3.654	0.023
	Log likelihood ratio	15.405	0.004
	Wald test statistic	14.616	0.006
2008	F-statistic	8.126	0.001
	Log likelihood ratio	26.924	0.000
	Wald test statistic	32.503	0.000
2013	F-statistic	2.599	0.069
	Log likelihood ratio	11.782	0.019
	Wald test statistic	10.394	0.034

			lnGVA_{UK per capita}		lnGVA_{L per capita}		lnGDP_{UK per capita}		lnATB_{UK per capita}
			t-statistic	P-value	t-statistic	P-value	t-statistic	P-value	t-statistic	P-value
At the level	ADF test statistic		-0.830	0.950	-1.910	0.620	-1.940	0.610	-0.170	0.930
	Critical value	1% level	-4.290		-4.360		-4.260		-3.650
		5% level	-3.560		-3.600		-3.550		-2.960
		10% level	-3.220		-3.230		-3.210		-2.617
At the 1^st difference	ADF test statistic		-6.500	0.000	-5.350	0.000	-4.740	0.000	-13.070	0.000
	Critical value	1% level	-4.290		-4.370		-4.270		-3.650
		5% level	-3.560		-3.600		-3.560		-2.960
		10% level	-3.220		-3.240		-3.210		-2.620
		Lag	AIC				SIC
Optimal lag structure		0	-3.970				-3.770
		1	-8.350^*				-7.380^*
		2	-7.770				-6.020

	Lag	Likelihood ratio error statistic	Probability	Rao F-statistic	Probability
Autocorrelation test	At lag 1	29.461	0.021	2.359	0.026
	At lag 2	18.384	0.302	1.213	0.324
	At lag 3	8.820	0.921	0.496	0.926
	At lag 1	29.461	0.021	2.359	0.026
	At lags 1-2	49.506	0.025	1.967	0.074
Normality test	Jarque-Bera	22.479
Normality test	Probability	0.004
Heteroscedasticity test	Chi-square	163.114
Heteroscedasticity test	Probability	0.417

	General VAR model				Parsimonious VAR model
	d(lnGVA_{UK per capita})	d(lnGVA_{L per capita})	d(lnGDP_{UK per capita})	d(lnATB_{UK per capita})	d(lnGVA_{UK per capita})	d(lnGVA_{L per capita})	d(lnGDP_{UK per capita})	d(lnATB_{UK per capita})
d(lnGVA_{UK per capita})	0.177 (0.213) [0.831]	0.123 (0.199) [0.616]	0.012 (0.047) [0.260]	-0.413^** (0.177) [-2.329]	0.008 (0.084) [0.093]	0.093 (0.177) [0.527]	0.012 (0.047) [0.260]	-0.413^** (0.177) [-2.329]
d(lnGVA_{L per capita} (-1))	1.263 (1.002) [1.260]	-1.731^* (0.936) [-1.850]	0.193 (0.219) [0.879]	1.801^** (0.835) [2.158]	1.173 (0.843) [1.390]	-1.661^* (0.861) [-1.928]	0.193 (0.219) [0.879]	1.801^** (0.835) [2.158]
d(lnGDP_{UK per capita} (-1))	0.070 (0.223) [0.313]	0.043 (0.208) [0.206]	-0.033 (0.049) [-0.669]	-0.083 (0.186) [-0.448]			-0.033 (0.049) [-0.669]	-0.083 (0.186) [-0.448]
d(lnATB_{UK per capita} (-1))	-0.371^* (0.199) [-1.861]	-0.179 (0.186) [-0.960]	-0.082^* (0.044) [-1.881]	-0.090 (0.166) [-0.544]	-0.346^** (0.174) [-1.982]	-0.187 (0.175) [-1.066]	-0.082^* (0.044) [-1.881]	-0.090 (0.166) [-0.544]
Constant	-0.046 (0.045) [-1.029]	0.078^* (0.042) [1.877]	0.028^*** (0.010) [2.923]	0.028 (0.037) [0.766]	-0.038 (0.038) [-1.002]	0.081^** (0.039) [2.059]	0.028^*** (0.010) [2.923]	0.028 (0.037) [0.766]
R²	0.226	0.224	0.165	0.342	0.160	0.217	0.165	0.342
Adjusted R²	0.071	0.069	-0.002	0.211	0.070	0.110	-0.002	0.211
Durbin Watson statistic	2.239	2.122	0.030	2.193	2.195	2.070	1.865	2.193
Log(likelihood)	114.376
AIC	-7.550
SIC	-6.575