1. Hugo Storm and Thomas Heckelei Institute for Food and Resource Economics (ILR), University of Bonn 150th EAAE Seminar “The spatial dimension in analysing the linkages between agriculture, rural development and the environment’ Edinburgh, UK, October 22-23, 2015 Local and regional spatial interactions in the analysis of Norwegian farm growth

2. Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 Farms interact!  Compete on the land market  Share knowledge  Interaction are local/spatial  Important for farm growth decision 2 Hypothesis and Objective  Identify effect of farm level interactions on growth  Particularly, identify how interaction influences direct payments effects  Separate actual interaction from spatially correlated omitted variables  Assess sensitivity of estimates with respect to the definition of neighbouring relationships (W) Hypothesis Objective Focus

3. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 “How can you distinguish between something unobserved and spatially correlated driving spatial correlation in y from the situation where y is spatially correlated because of direct interaction between outcomes? Further, how can you tell whether an individual is affected by the behaviour of their group, or by the characteristics of their group when group behaviour depends on the characteristics of the group?” Gibbons and Overman (2012). Mostly Pointless Spatial Econometrics? Journal of Regional Science 52(2):172–191. 3 Identification Problem unobserved spatial correlated variable Actual interaction Indirect (endogenous) Direct (exogenous) SLX (instead of SAR) model to identify overall interaction effect focus in the following… Geographic conditions, farm structure land market machinery

4. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 Farm level data covering all farms in Norway Spatially explicit Dep. var. absolute growth in arable land between 1999 and 2009 (in daa = 1/10 ha) Empirical model The spatially lagged explanatory variable (SLX) model (general) Analysing farm growth of surviving farms (Subsample OLS) (n ~ 31.000) Data Model 4

5. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 “Classical” SLX Model 5 Local and regional neighbourhood unobserved spatial correlated variable Actual interaction Problem: Omitted variable bias Unobserved spatial correlated variables might be correlated with X and y Example: Direct Payment But coupled payments might be correlated to intensity of production or farm structure in the region which itself effects growth Hypothesis: own payments ↑ neighbouring payments ↓ Hypothesis: own payments ↑ neighbouring payments ↓ From above

6. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 6 Results of “classical” SLX model Estimated effect on growth for different W L Neighbouring direct payments Neighbouring arable land (in daa = 1/10 ha) Coefficient of own direct payments around 0.11 Coefficient of own arable land around -0.10 Problem Likely to capture different effects (actual interaction / unobserved variables) Problem Likely to capture different effects (actual interaction / unobserved variables)

7. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 “Classical” SLX Model 7 Local and regional neighbourhood unobserved spatial correlated variable Actual interaction Problem: Omitted variable bias Unobserved spatial correlated variables might be correlated with X and y Example: Direct Payment But coupled payments might be correlated to intensity of production or farm structure in the region itself effecting growth Hypothesis: own payments ↑ neighbouring payments ↓ Hypothesis: own payments ↑ neighbouring payments ↓ Alternative Model: Differentiate between local W L and regional W R neighbourhood Solution approach From above

8. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 8 Local and regional neighbourhood Local neighbourhood, W L (30km) Regional neighbourhood, W R (ring 30 to 60km) Intended to capture actual interaction (land market / knowledge) Intended to capture confound variation (farm structure / geographic) Random sample of 500 neighboring farms. Total number of neighb. farms is 1,540 and 5,122 for the local and regional neighb., respectively. Source Maps: http://gpso.de/maps / Map Data: 2015 OpenStreetMap http://gpso.de/maps /

9. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 9 Spatial correlation in expl. Var. Radius of W L dPayarablegenChangehasMilk 500 m0.30540.30560.25290.3526 2 km0.50200.60630.47620.5056 3 km0.59900.68320.58930.5780 4 km0.65190.72390.66900.6215 5 km0.68860.74920.72610.6525 6 km0.72470.77450.77940.6841 8 km0.75660.79520.82810.7133 10 km0.77940.81130.85880.7370 15 km0.82180.83770.89600.7797 20 km0.85090.85790.91940.8097 25 km0.87360.87760.93370.8362 30 km0.89410.89800.94500.8623 Correlation coefficients between local W L and regional neighbourhood W R (30 to 60km ring)

10. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 10 Results local and regional neighb. Neighbouring direct payments Neighbouring arable land (in daa = 1/10 ha) Local neighb.Regional neighb. Coefficient of own direct payments around 0.11 Coefficient of own arable land around -0.10 Model:

11. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 Estimated coef. of WX sensitive to neighbouring definitions Sensitivity likely to be cause by different types of effects (actual interaction vs. unobserved variables) Considering different neighbourhoods (local/regional) leads to opposite effects of WX despite high correlation Negative/positive effects of direct payments in local/regional neighbourhood indicate interaction on the land market/unobserved variables Conclusion and Outlook Analyse effects of spatially correlated omitted variables and direct interaction effects using generated data … Conclusion Outlook 11

12. Thanks!

13. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 13 Descriptive statistics CodeUnitMeanMedianminmaxstd Change in Arable land 1999 to 2009 delArabledaaa32.343.00-1247.005061.00122.01 Age of the farm holderageyear48.2048.007.0090.0010.99 Arable landarabledaa a 158.19125.000.012994.00136.11 Observed labor inputobsLabohour2642.672500.008.0052330.001881.48 Estimated labor requirementreqLabohour2391.602107.9717.4242873.531805.32 Total direct paymentsdPay1000 Nkr204.95195.710.001252.47133.23 Total market returnmRet1000 Nkr-40.45-37.41-2168.291403.7672.81 Ratio observed over estimated labor requirement laboObs/Reqratio1.281.110.0065.770.95 Dummy if farm has milk cowshasMilkbinary0.420.00 1.000.49 … has sheephasSheepbinary0.330.00 1.000.47 … has sowshasSowsbinary0.060.00 1.000.24 … has poultryhasPoultrybinary0.010.00 1.000.09 Tot. Direct pay. per total farm area dPayUaar 1000 Nkr / daa a 1.28 0.0040.740.80 Dummy if a generational transfer took place genChangebinary0.300.00 1.000.46 Regional dummy b for "Other regions in Eastern Norway" argR12binary0.190.00 1.000.39 … "Jæren"argR21binary0.040.00 1.000.21 … "Other regions in the counties of Agder and Rogaland" argR22binary0.090.00 1.000.28 … "Western Norway"argR32binary0.210.00 1.000.41 … "Lowlands in Trøndelag"argR41binary0.080.00 1.000.27 … "Other regions in Trøndelag"argR42binary0.080.00 1.000.27 … "Northern Norway"argR52binary0.090.00 1.000.28

14. Local and regional spatial interactions in the analysis of Norwegian farm growth Hugo Storm and Thomas Heckelei 150th EAAE SeminarEdinburgh, UK, October 22-23, 2015 14 Regression results W_km2W_km15W_km30 VariableCoefp-valueCoefp-valueCoefp-value const-12.02080.7892-49.22410.3143-133.03300.0123 age-3.78460.0000-3.84780.0000-3.69800.0000 age^20.03140.00000.03180.00000.03030.0000 arable-0.10230.0000-0.10950.0000-0.10620.0000 obsLabo0.00070.29950.00110.12510.00070.3173 reqLabo0.00430.00000.00340.00060.00390.0001 dPay0.10790.00000.12340.00000.11420.0000 mRet-0.02660.0704-0.02000.1816-0.02110.1637 laboObs/Req1.78850.07301.32450.19231.45850.1565 hasMilk-13.59590.0000-14.86460.0000-14.11240.0000 hasSheep-2.84460.0159-2.92120.0139-3.54800.0029 dPayUaar4.29810.00024.15350.00044.43070.0002 genChange18.09790.000017.75110.000018.65070.0000 …. W_dPay-0.06990.0013-0.17030.0003-0.21880.0015 W_arable0.09140.00000.16060.00000.20520.0000 W_reqLabo-0.00270.0378-0.00010.97410.00150.6638 W_hasMilk13.04650.000326.75950.002538.03010.0037 W_age0.31760.00001.47350.00053.47800.0000 W_genChange-20.76960.0000-86.57040.0000-127.87340.0000 …. Wring_dPay0.15530.07710.21360.01850.16270.1028 Wring_arable0.06280.15240.00030.9954-0.05430.3074 Wring_reqLabo0.00720.15190.00860.10200.01300.0246 Wregion_hasMilk-74.27480.0000-82.61390.0000-70.80470.0003 Wring_age2.08350.02611.71890.08151.49310.1459 Wring_genChange-52.16220.0105-1.45720.946817.78920.4705 …. n32043 ---30940 ---30257 --- AIC8.5897 ---8.6248 ---8.6472 --- rsqr0.0512 ---0.0522 ---0.0516 --- rbar0.0501 ---0.0510 ---0.0504 ---