Direkt zum InhaltDirekt zur SucheDirekt zur Navigation
▼ Zielgruppen ▼

Humboldt-Universität zu Berlin - Faculty of Life Sciences - Department of Agricultural Economics

Projects

of the FORLAND research unit:
Agricultural Land Markets - Efficiency and Regulation

 

SP 1: Multivariate modeling of rental rates and prices of farmland using structured additive conditional copula regression
Oliver Mußhoff

SP 2: Market integration and border effects in agricultural land markets
Martin Odening / Matthias Ritter

SP 3: Ethical issues in agricultural land markets
Vladislav Valentinov

SP 4: Is regulating agricultural land prices warranted? - A microstructure analysis of its impact and justification
Silke Hüttel / Axel Werwatz

SP 5: Understanding farmers’ land use behaviour under different institutional settings
Marianne Penker / Klaus Salhofer

SP 6: Can agricultural land market regulations fulfill their promises? Agent-based simulation studies for selected German regions
Alfons Balmann

SP 7: Spatiotemporal analysis of farm-level and environmental outcomes of land markets
Tobia Lakes / Daniel Müller

 

Subproject 1:

Multivariate modeling of rental rates and prices of farmland using structured additive conditional copula regression

Prof. Dr. Oliver Mußhoff, Farm Management Group, Georg-August-Universität Göttingen

This subproject contributes to the overall objective of the research unit by empirically analyzing the determinants and statistical dependence between rental rates and farmland prices. A unique feature of this subproject is that we study both land rental markets and farmland markets. In efficient land and financial markets, rental and sale prices should be co-integrated. Empirical studies provide evidence that farmland price and rental rate movements are not in accordance with the relationship suggested by asset pricing models. Besides testing whether speculative bubbles can explain the discrepancy between theoretical farmland values and empirically observed farmland values, this subproject uses conditional copula regression models to study the relationship between rental and sales prices of farmland. More specifically, we will deal with the following objectives and research questions:

  1. Are speculative bubbles characteristic of land markets?
    We will test if speculative bubbles can explain the discrepancy between theoretical farmland values and empirically observed farmland values (e.g., using unit root tests).
  2. What are the determinants of agricultural land prices and farmland rental rates?
    We will identify the determinants of rental rates and prices of farmland, not only with respect to the mean, but with a particular focus on their influence on higher moments of the response distribution, such as the variance. In contrast to existing hedonic pricing studies, we analyze all distributional parameters within a regression setting, which allows us to provide a more detailed analysis of farmland prices and rental rates.
  3. How can the relationship between rental rates and farmland prices be explained?
    We will explicitly analyze the statistical dependence between rental rates and farmland prices. Relating the coefficient that governs the strength of their dependence to economic variables within a regression setting allows us to investigate the relationship between farmland prices and rental rates in more detail and to shed light on the inconsistency between trends in farmland prices and rental rates.
  4. Is there a geographic variation of the relationship between agricultural land prices and farmland rental rates?
    We will investigate the spatial distribution of different distributional parameters of farmland rental rates and of parameters that govern the relationship between agricultural land prices and rental rates. With our analysis, we will offer a more regional perspective at a highly disaggregated spatial level and provide new insights into within-country dynamics.

The subproject is empirically based on an extended dataset of land sale and land rent transactions, including information about the land’s location, size, type, and soil quality as well as about the year of transaction. This study uses data from the German federal states of Lower Saxony, Brandenburg, and Saxony-Anhalt.

Keywords: Agricultural Economics, Land Markets, Relationship between Rental Rates and Farmland Prices

 

Subproject 2:

Market integration and border effects in agricultural land markets

Prof. Dr. Martin Odening, Farm Management, Humboldt-Universität zu Berlin
JProf. Dr. Matthias Ritter, Quantitative Agricultural Economics, Humboldt Universität zu Berlin

This subproject contributes to the overall objective of the research unit by empirically studying spatial price diffusion of agricultural land markets. We borrow the notion of spatial market integration from commodity price analysis and question whether traditional concepts, such as the law of one price, are meaningful to assess the economic efficiency of agricultural land markets. Moreover, we aim at a better understanding of regional disparities in agricultural land markets by adapting and using models from economic geography. Thus, our results will provide insights into existing market rigidities and potential needs for regulations of land markets. More specifically, we will deal with the following objectives and research questions:

  1. Can the concept of spatial market integration be adapted to agricultural land markets?
    We will scrutinize the theoretical preconditions of the law of one price and examine the effect of their violations in the context of land markets. Together with subproject 7 (Lakes/Müller), we will adapt concepts from economic geography to explain the coexistence of multiple spatial equilibria.
  2. How can land price convergence clubs be identified?
    Using various spatio-temporal price diffusion models, we will identify regions showing similar price dynamics and investigate to what extent these regional markets are spatially integrated. The empirical analysis will be conducted for Germany and the Czech Republic.
  3. How can the existence of convergence clubs on agricultural land markets be explained?
    Potential reasons could be regionally different roles of non-agricultural investors, farm size structures, or production structures. Special attention will be given to the impact of borders on the convergence of land prices. We expect that price convergence appears much faster in regions closer to the border because of a direct spillover of prices. The analysis will be carried out for Eastern and Western Germany as well as for the German-Czech border. The expected results are not only interesting from a historical perspective, but also for a better understanding of the functioning of land markets. A better understanding of the determining factors, in turn, helps to forecast the future development of regional land prices.
  4. From a methodological viewpoint, which model is most suitable for the analysis and prediction of spatial price development?
    Three different price diffusion models that cover a wide range of the current literature will be compared: A multifactor error structure model allowing for common factors influencing price development; a nonlinear time varying factor model considering time-dependent and random effects of one common factor; and a spatio-temporal price diffusion model considering the effects of dominant regions and borders.

Keywords: Agricultural Economics, Land Markets, Spatio-temporal Price Analysis

 

Subproject 3:

Ethical issues in agricultural land markets

PD Dr. Vladislav Valentinov, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale)

Agricultural land markets in the countries under investigation are marked by the dramatic increase of land prices and rents, the growing role of non-agricultural investors, the emergence of large-scale holding structures, and the increasing demand for the conversion of agricultural land to non-agricultural uses. Each of these trends is often felt to have moral significance. The present subproject is aimed at explicating this significance, exploring the possibilities and limits of public regulation of agricultural land markets, and developing conceptual tools to address moral dilemmas whose complexity runs up against the limits of regulatory instruments.

This subproject explores the contrast between the economic and non-economic standpoints to assessing the performance of agricultural land markets. While the utilitarian vision of land buttresses the economic standpoint, a number of currently prevailing land market policy goals in Germany and other EU countries stretch the limits of the utilitarian thinking. The promotion of the broad dispersion of land ownership, the control of the rise of prices and rents, and priority of agricultural uses of agricultural land are cases in point. Moreover, in cases of trade-offs between economic efficiency and alternative moral criteria, such as social and ecological sustainability, the utilitarian doctrine will tend to questionably prioritize efficiency at the cost of downplaying various sustainability concerns. Land grabbing is one example where alternative moral criteria are particularly likely to collide in dramatic ways. On the other hand, some other land market policy goals, such as avoiding market power and improving transparency on agricultural land markets, are fully consistent with the utilitarian goal of optimizing the allocation of agricultural land through the market mechanism. Besides, the economic standpoint as such is by no means inconsistent with the seemingly non-utilitarian moral goals such as the protection of biodiversity. While various instruments can be used to make the price mechanism more responsive to such goals, there are no guarantees that these instruments are sufficient. It is for this reason that the contrast between the economic and non-economic standpoints remains an urgent and ongoing task, both for practice and theory.

The subproject’s strategy is to draw on Niklas Luhmann’s theory of “autopoietic” social systems which maintain a precarious relationship to their environment, societal and natural alike. The prime example of such a system is the land market that exhibits considerable autonomy from the societal and natural environments and thus is prone to overstraining their carrying capacities. The political and legal systems hold the potential to forestall this overstraining but are subject to autopoietic closure of their own. In the first step of the work program, an ethical mapping exercise will be undertaken to take full account of the existing utilitarian and non-utilitarian explanations of agricultural land markets. In the second step, discourse analysis methods will be applied to stakeholder interviews as well as to the selected German mass media. The third step involves the organization of stakeholder workshops in the formats informed by the “critical systems heuristics” and the “integrative propositional analysis”. In the last step, the previous results will be summarized and elaborated in the construction of the “social fabric matrix”.

Keywords: agricultural land markets; land ethics; business ethics; agricultural sociology; moral dilemmas; systems theory; utilitarianism; discourse analysis; social fabric matrix

 

Subproject 4:

Is regulating agricultural land prices warranted? - A microstructure analysis of its impact and justification

Prof. Dr. Silke Hüttel, University Bonn
Prof. Axel Werwatz, Ph.D, Technical University Berlin

The justifications of land market regulation go well beyond classical economic concerns such as efficiency. In recent years, a primary concern both of existing as well as proposed regulation of the farmland market is the risk of farmers being “priced out of the market” for a farmland parcel. This risk is perceived as having considerably increased due to two trends: an increasing presence of non-agricultural investors in farm-land markets and an increasing pressure on farm land from the world-wide tendency of urbanization and urban sprawl. Against this backdrop, we will estimate the price effects of existing regulation of the farm-land market as well as price effects of these drivers for new and tougher regulation. These issues are interrelated since existing regulation already aims at protecting farmers from such pressures. We thus look at this topic from two perspectives: does existing regulation work and is there evidence for the perceived pressures that may warrant further regulation?

Our project is organized in three work packages (WP): (1) existing regulation, (2) non-farm investors and (3) urban sprawl. They are not only closely linked topically but also share a common methodology. Throughout we use land prices as the outcome variable, focus on estimating the causal effect of our three “treatments” and control for other determinants of prices in a hedonic regression framework. These regressions will be directly estimated from transactions data and—if feasible—augmented by alternative estimators of treatment effects from non-experimental data such as matching or the regression discontinuity design.

In WP 1, we estimate the price effects of existing regulation using data from the state of Baden-Wuerttemberg. To identify the price effects of regulation we exploit the regulatory variation among the approximately 900 local counties. Moreover, the current regulation has been tightened within our observation window, providing us with additional identifying variation.

In WP 2, we investigate the price effect of non-agricultural investors in eastern Germany and the Czech Republic. The transformation process constituted an attractive opportunity for non-agricultural investors to participate in agricultural land markets and is a yet under-researched “field laboratory”. We will methodologically go beyond the conventional treatment effect paradigm to consider the market micro-structure and the auction set-up in a structural econometric model.

In WP 3, we investigate the price effect of urban sprawl in the Berlin-Brandenburg region. We thus exploit, like economic researchers from other fields, the fall of the wall as a `natural experiment’ that—in our case—opened up new growth possibilities for Germany’s capital. Prices for peri-urban farmland in the Berlin region may thus be pushed upward by its `option value’ from being subsequently converted to urban use. This option effect should be decreasing with distance from city borders and city business districts.

Keywords: Agricultural Economics, Land Auctions, Causal Impact Evaluation

 

Subproject 5:

Understanding farmers’ land use behaviour under different institutional settings

Marianne Penker and Klaus Salhofer, Institute of Sustainable Economic Development, University of Natural Resources and Life Sciences, Vienna, Austria

This project investigates institutional drivers of farmers’ land use behavior. We study the influence of two formal institutions, property rights in land and agri-environmental schemes (AES) on farmers’ behavior toward soil conservation.

It has been argued since a long time, that tenancy as compared to land ownership leads to suboptimal resource allocation and soil degradation. The economic rational for this is the difference in length of a farmer’s planning horizon. Given that rental shares are high in many EU countries, it is important to understand the impact of land ownership on farmers’ land use behavior and investments in land. AES are understood as an appropriate response to negative external effects of agricultural production and, therefore, may be a measure to mitigate insecure land tenure effects.

Formal institutions and economic considerations are important for farmer’s decisions, but social norms, beliefs and values also shape farmers’ motivations and behavior. Therefore, to fully understand the institutional drivers of farmers’ land use behavior, we apply economic and socio-psychological theories and models in four work packages.

WP1 “Plot-level analysis of property rights and land use behavior” investigates if farmers are more likely to plant erosion-prone crops and use less crop rotation on rented land as compared to owned land based on plot-level data. Moreover, we examine the association between land ownership and participation in AES that aim at enhancing soil conservation.

In WP2 “Economic and environmental efficiency of farm households under different land tenure”, we combine a household production model and stochastic frontier models based on distance functions. We apply this novel approach to reveal trade-offs between economic and environmental efficiency and its interaction with land ownership and AES.

In WP3 “Socio-psychological analysis of farmers’ land use behavior” we use explorative interviews and a structured survey of farms to understand how formal and informal institutions shape farmers’ motivations for soil conservation based on concepts of human-nature-relationships (HNR).

In WP4 “Conceptual model of institutionally shaped land use behavior and farming types” we use the outcome of WP1 – WP3 to identify different farming types and how they are attracted or crowded out by different types of soil conservation policies.

Our main contributions are: i.) we take an integrative approach by combining economic and socio-psychological models; ii.) we enhance the eco-efficiency literature by developing a model that better fits the decisions within family-farm households; iii.) we explore the issue by applying the HNR approach which stresses farmers’ relation with nature; iv.) we apply all this based on two rather exceptional data sets; a nationwide, multiple-year dataset on plot level and farm-level booking keeping data linked with survey data compiled in this project.

Keywords: Agricultural Sociology, Agricultural Economics, Property Rights, Environmental Efficiency, Soil Conservation, Human-Nature-Relationships

 

Subproject 6:

Can agricultural land market regulations fulfill their promises? Agent-based simulation studies for selected German regions

Prof. Dr. Alfons Balmann, IAMO, Halle

In many countries, agricultural land markets are regulated through a specific legislation and opportunities for interventions by public authorities. Many regulations are justified by objectives such as to improve the efficiency of agricultural production, to serve societal interests or to protect existing farms or farm structures. In recent years, a number of proposals were and are discussed within the EU, including Germany, suggesting a stronger regulation. These proposals were on the one hand driven by substantially increasing land sales and rental prices. On the other hand, the proposals resulted from concerns that non-agricultural investors could buy agricultural land in substantial amounts as well as affect existing farm structures through acquisitions of corporate farms.

While there exists a broad range of literature on the reasons and motives for land market regulations, there is yet limited research regarding the question whether land market regulations can really fulfill their promises. In particular, regulations may fail due to complexities related to emergent phenomena of structural change such as path dependences, trade-offs between different objectives, and trade-offs regarding the objectives at different points in time. These complexities limit the opportunities for theoretical research and due to the problem to identify adequate counterfactuals also those for empirical research. Therefore, this subproject proposes to use agent-based simulations with the Agricultural Policy Simulator AgriPoliS. AgriPoliS is an established model of structural change in agriculture. It allows to analyze the implications of specific land market regulations for selected regions by considering land rentals, heterogeneous farms, dynamics and endogenous structural change. Beyond the use model and relevant extensions of this model, the proposed analyses require conceptual work regarding criteria to assess the effectiveness of regulations related to structural, sustainability and resilience goals. The proposed simulations require specific designs for experimental settings which allow for a systematic analysis of regulations considering a broad range of potential assumptions as well as the multidimensional effects of regulations on the aggregate and the individual level.

The proposed simulations will particularly address two stylized kinds of regulations. These are on the one hand absolute and relative price limits for rental prices and on the other hand absolute and relative limitations to the size of every farm’s land bank. The hypotheses to be analyzed include for instance that regulations cause welfare losses which in the long run even increase and that smaller and less efficient farms may only benefit in the short run at the risk of losses in the long run.

Keywords: Agricultural Economics, Land Markets, Regulation, Agent-based modelling

 

Subproject 7:

Spatiotemporal analysis of farm-level and environmental outcomes of land markets

Prof. Dr. Tobia Lakes, Applied Geoinformation Science, Humboldt-Universität zu Berlin
PD Dr. Daniel Müller, Leibniz Institute of Agricultural Development in Transition Economies (IAMO) and Geography Department, Humboldt-Universität zu Berlin

In this subproject, we aim to better understand land market outcomes by examining the spatial and temporal associations between changes in land prices with changes in agricultural land use, ownership, farm structures, and environmental characteristics. We will analyse linkages between these variables with retrospective and prospective approaches that exploit spatial data and account for variation over time during the last decade. In our data-driven approach, we will use spatial statistics and machine learning to extract patterns and associations in two agriculturally important federal states of Germany and in the Czech Republic. Together with other subprojects, we will develop scenarios with stakeholders that serve to explore alternative future land market developments and policy regulations. The scenario outcomes are fed into a spatial allocation models to simulate future land use and environmental indicators. Our subproject is situated at the interface of economic geography, agricultural sciences, and applied geoinformation science. The results are expected to contribute valuable spatiotemporal understanding for the different institutional contexts that may justify land market interventions and assist in their spatial targeting.

  1. What are the spatiotemporal outcomes of land markets with respect to farm size, ownership, land use, and the environment?
    We will use spatial clustering and machine learning approaches to explore and disentangle the associations between changes in land prices with farm characteristics as well as environmental indicators. The resulting cluster maps permit, together with insights from subproject 2 (Odening/Ritter), a much better and area-wide understanding of where and why spatial clusters of relevant land market outcomes emerge.
  2. How will alternative future developments of land markets impact on farm-level characteristics, land use, and the environment?
    We will develop a spatial model at the level of farm plots. The model allocates demand for land based on land suitability, following the theories from Ricardo and von Thünen as well as insight from subprojects 2, 4, and 6. With the help of stakeholder workshops and the results from other subprojects, we will approximate demand for land, and thus price, under alternative future scenarios, and use the allocation model to simulate future land use for each scenario.
  3. Are there characteristic differences in land market outcomes across German federal states and countries?The retrospective as well as the prospective analysis, developed for the federal state of Brandenburg, will be replicated in the federal state of Lower Saxony and in the Czech Republic. This outscaling permits comparative insights for different institutional and political settings and advances our understanding of the contributions of historic legacies and path dependency on farm-level and environmental outcomes of land market variations.

Keywords: Geography, Agriculture sciences, Spatiotemporal patterns of land market outcomes, Environmental Impacts, Scenarios analysis, Land-use modelling.