Prce Formaton on Agrcultural Land Markets A Mcrostructure Analyss Martn Odenng & Slke Hüttel Department of Agrcultural Economcs, Humboldt-Unverstät zu Berln Department of Agrcultural Economcs, Unversty Rostock Paper presented at the 60 th Annual AARES Conference, 2-5 February 206, Canberra
Development of Land Prces n Germany (Source: Destats) 2 Prce ( /ha) West East BVVG 30000 27000 24000 2000 8000 5000 2000 9000 6000 3000 0
Relevant lterature 3 Classcal Hedonc land prcng e.g. Palmqust & Danelson (989), Huang et al. (2006) Productvty characterstcs Locaton & regonal characterstcs Envronmental varables Polcy mpact / subsdes Market (mcro)structure Market power Cotteleer & Gardebroek (2008) Role of market mechansm e.g. Lusht (996), Mayer (996), Quan (2002) Forced sales e.g. Allen & Swsher (2000), Campbell et al. (2009)
Outlne 4. Motvaton 2. Forced sales and farmland prces 3. Prce formaton n agrcultural land auctons 4. Conclusons
Forced Sales: Hypotheses 5 Interference of two, possbly opposed effects. Pressured sale prce 2. Aucton effect prce 3. Net effect foreclosure prce?
Emprcal Applcaton 6 Regon: State of Brandenburg/Germany Data Source: Expert panel (Oberer Gutachterausschuss) Indvdual transacton data: 26,786 observatons, % foreclosures Perod: /2000 9/20 Varables: Prce, sol qualty, plot sze, locaton (county), date of sale
Econometrc approach 7. Regresson model ln p 0 ATT x 0 n 0 n u p n x : [sol qualty ndex, sze, sze², 8 county dummes, tme dummes] n ˆ 0 x 2. Matchng Drect covarate matchng K-nearest neghbor Mahalanobs dstance ATT n n match p p
Results: Effects of Forced Sales (ATT) 8 Year Observed prce forced sales Observed prce nonforced sales Counter factual (regresson) Counter factual (matchng) Prce dfference (regresson) Prce dfference (matchng) () (2) (3) (4) ()-(3) ()-(4) 2000 3,246 2,40 2,354 2,764 892 744 200,5 2,390 2,445,985 -,294-834 2002 2,692 2,450,958 2,3 734 508 2003 2,368 2,400 2,075 2,477 293-0 2004,960 2,340,878 2,355 82-395 2005 2,595 2,450,969 2,77 626 42 2006,589 2,470 2,279 2,409-690* -884* 2007 3,48 2,620 2,237 2,602,8* 85* 2008 3,437 3,070 2,584 2,956 853* 48 2009 3,83 3,470 2,902 3,34 28 49 200 4,070 3,60 3,295 3,629 775 440 20 5,25 3,960 3,59 3,625,966* 500* Total 3,075 2,844 2,475 2,78 600* 282*
Land Market Auctons n Saxony-Anhalt 9 LGSA (Landgesellschaft Sachsen-Anhalt) Land admnstraton agency. Prvatzaton of formerly state-owned land Frst prce sealed bd aucton wth publc tenders Tenderng results of the LGSA from 2003-200; ~760 transactons (arable and grassland) Avalable nformaton: prce, sze, locaton, sol qualty, number of bds, bdder status (resdental farmer, non-agrcultural nvestor)
Prces formaton on land auctons: Hypotheses 0 Aucton theory: Optmal bd ncreases wth number of bdders hgher number of bds = hgher prce (prvate value aucton) Dfferent optmal bds among dfferent groups of bdders: non-agrcultural bdders: hgher optmal bds = hgher prce
Results: Spatal Lag Model Estmated coeffcent Sol qualty 0.0*** Plot sze (lnear) (ha) 0.03 Plot sze (quadratc) 0.000 Share arable land 0.44*** Number of bds 0.033*** Share of bds from agrculture -0.27*** Local buyer 0.06* Dummy 2008 (Bass 2003) 0.203*** Dummy 2009 (Bass 2003) 0.286*** Dummy 200 (Bass 2003) 0.370*** ***, ** and * denote statstcal sgnfcance at, 5 and 0 percent, respectvely
Conclusons 2 Market structure and characterstcs play a role for the market outcome Prces on auctons appear hgher than on search markets Share of non-agrcultural bdders drves up prces Prces are hgher f wnnng bdder s a resdent Land prces n Germany can be well explaned by market fundamentals (no evdence for land prce bubbles) No need for tghter regulatons of land markets
3 Backup Sldes
Data: Summary Statstcs of the Farmland Prces and Characterstcs 4 Group Non-forced sales N=26,502 Forced sales N=284 Total N=26,786 Statstc Prce ( /hectare) Sol qualty arable land Sol qualty grassland Area (hectares) Mean 2,844 26.34 25.5 4.38 Std. devaton,572.9 7.03 0.22 Mn. 58 0,0 Max. 9,397 80 60 427.77 Mean 3,074 26.98 23.46 3.08 Std. devaton 2,588.0 6.5 5.82 Mn. 54 8 0.0 Max. 20,835 72 40 47.56 Mean 2,847 26.34 25.49 4.36 Std. devaton,586.9 7.02 0.8 Mn. 58 0,0 Max. 20,835 80 60 427.77 Source: Own calculatons based on data from Oberer Gutachterausschuss Brandenburg.
EUR/hectare Number of observatons Data: Development of farmland prces 5 6000 forced sales observatons regular observatons 4000 5000 forced sales prces regular prces 3500 3000 4000 2500 3000 2000 2000 500 000 000 500 0 2000 2002 2004 2006 2008 200 Year 0
Results: Hedonc prce model 6 Dependent varable log prce ( /m²) Coeffcent estmates P-value Sol qualty arable land (AZ) 0.006 0.000 *** Area (hectares) -0.002 0.000 *** Area squared (hectares).33e-05 0.00 *** D 200-0.06 0.364 D 2002 0.03 0.462 D 2003 0.026 0.63 D 2004-0.008 0.63 D 2005 0.075 0.305 D 2006 0.025 0.33 D 2007 0.086 0.000 *** D 2008 0.237 0.000 *** D 2009 0.375 0.000 *** D 200 0.426 0.000 *** D 20 0.498 0.000 ***
Data: Mean prces for countes 7 Regonal average land prces n /ha, 2008-200 Source: Own calculatons; data provded by Oberer Gutachterausschuss Brandenburg and Landesamt für ländlche Entwcklung, Landwrtschaft und Flurneuordnung.
Econometrc approach 8 Objectve: Estmaton of the average treatment effect on the treated (ATT) ATT E p Ths can be expanded to p 0 d 0 0 0 p d E p d 0 E p p d E p d E p d 0 E observed dfference n prces ATT selecton bas Condtonal ndependence assumpton (CIA) p 0, p d x
Explanatory varables: summary statstcs 9 mean s.d. mn max sol qualty (0-02) 64 22 23 0 % arable land 85 28 0 00 lot sze (ha) 7.25 3.47 0.06 26.48 arable land (ha) 6.39 3.54 0 25.86 grassland (ha) 0.67.79 0 5.85 # of bds 4 3 7 % farmers' bds 89 7 30 00 prce ( /sq m) 0.82 0.47 0. 2.6 acceptance bd n 48% of the cases from tenant N=722
Econometrc procedure 20 Spatal lag model ln prce = ρ W j ln prce j + x k β k j k + d l δ l county + d t δ t year + e l t x: explanatory varables; e: error term; W: spatal weghts; ρ: mpact of neghbourng land prces
Open questons & further research 2 How do buyer and seller characterstcs affect prce formaton? What are the motves of non-agrcultural nvestors to buy land? What s the effect of farm takeovers on land markets? Do market power and strategc decson makng play a role n (local) land markets? Are (local) land markets spatally ntegrated or separated?