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  • 1.
    Balmann, Alfons
    et al.
    Leibniz-Institut für Agrarentwicklung in Transformationsökonomien (IAMO), Halle (Saale).
    Demoustier, Jana
    Leibniz-Institut für Agrarentwicklung in Transformationsökonomien (IAMO), Halle (Saale).
    Grau, Aaron
    Humboldt-Universität zu Berlin (HUB).
    Graubner, Marten
    Leibniz-Institut für Agrarentwicklung in Transformationsökonomien (IAMO), Halle (Saale).
    Hüttel, Silke
    Rheinische Friedrich-Wilhelms-Universität Bonn.
    Kahle, Christoph
    Rheinische Friedrich-Wilhelms-Universität Bonn.
    Müller, Daniel
    Leibniz-Institut für Agrarentwicklung in Transformationsökonomien (IAMO), Halle (Saale); Humboldt-Universität zu Berlin (HUB).
    Odening, Martin
    Humboldt-Universität zu Berlin (HUB).
    Plogmann, Jana
    Humboldt-Universität zu Berlin (HUB).
    Ritter, Matthias
    Humboldt-Universität zu Berlin (HUB).
    Seifert, Stefan
    Rheinische Friedrich-Wilhelms-Universität Bonn.
    Marktmacht in landwirtschaftlichen Bodenmärkten – Bedeutung, Messung, Abgrenzung2020Report (Other academic)
  • 2.
    Balmann, Alfons
    et al.
    Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle, Germany.
    Graubner, Marten
    Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle, Germany.
    Müller, Daniel
    Hüttel, Silke
    Institute of Food and Resource Economics, University of Bonn, Bonn, Germany.
    Seifert, Stefan
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Plogmann, Jana
    Georg-August-Universität Göttingen, Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Market Power in Agricultural Land Markets: Concepts and Empirical Challenges2021In: German Journal of Agricultural Economics (GJAE), ISSN 0002-1121, E-ISSN 0515-6866, Vol. 70, no 4, p. 213-235Article in journal (Refereed)
    Abstract [en]

    This paper provides review about challenges and opportunities to assess and quantify market power in agricultural land markets. Measuring land market power is challenging because the characteristics of this production factor hinder the direct application of familiar concepts from commodity markets. Immobility, fixed availability, and large heterogeneity of land and potential users contradict assumptions of fictitious point market for homogeneous goods. Moreover, the use of concentration indicators for policy assessments is hampered by two problems. First, defining the relevant regional size of the market is challenging and concentration indicators are not robust with regard to market size and number of actors. Second, high concentration of land ownership or land operation may point at potential market power, but it may also be the result of an efficient allocation of land due to structural change in agriculture. The aforementioned challenges are illustrated with a case study for the Federal State of Brandenburg in Germany. Using available data for land sales, a regression analysis reveals a negative relationship between land use concentration and farmland prices. This result can be interpreted as an indication of market power on the buyer side in agricultural land markets. However, it is hardly possible to translate this finding into recommendations for land market regulations because the evaluation of the potential misuse of dominant positions in land markets requires a case-specific analysis. Providing evidence for the exertion of market power in land markets is extremely complex and deserves further attention from researchers and politicians.

  • 3.
    Cao, Xiaofeng
    et al.
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Okhrin, Ostap
    Chair of Statistics and Econometrics, Technische Universität Dresden, Dresden, Germany; SFB 649, School of Business and Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Odening, Martin
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Modelling spatio-temporal variability of temperature2015In: Computational statistics (Zeitschrift), ISSN 0943-4062, E-ISSN 1613-9658, Vol. 30, no 3, p. 745-766Article in journal (Refereed)
    Abstract [en]

    Forecasting temperature in time and space is an important precondition for both, the design of weather derivatives and the assessment of the hedging effectiveness of index based weather insurance. In this article, we show how this task can be accomplished by means of Kriging techniques. Moreover, we compare Kriging with a dynamic semiparametric factor model (DSFM) that has been recently developed for the analysis of high dimensional financial data. We apply both methods to comprehensive temperature data covering a large area of China and assess their performance in terms of predicting a temperature index at an unobserved location. The results show that the DSFM performs worse than standard Kriging techniques. Moreover, we show how geographic basis risk inherent to weather derivatives can be mitigated by regional diversification.

  • 4.
    Cao, Xiaofeng
    et al.
    Humboldt-Universität zu Berlin, Germany.
    Okhrin, Ostap
    Humboldt-Universität zu Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Modelling spatio-temporal variability of temperature2014Report (Other academic)
    Abstract [en]

    Forecasting temperature in time and space is an important precondition for both the design of weather derivatives and the assessment of the hedging effectiveness of index based weather insurance. In this article, we show how this task can be accomplished by means of Kriging techniques. Moreover, we compare Kriging with a dynamic semiparametric factor model (DSFM) that has been recently developed for the analysis of high dimensional financial data. We apply both methods to comprehensive temperature data covering a large area of China and assess their performance in terms of predicting a temperature index at an unobserved location. The results show that the DSFM performs worse than standard Kriging techniques. Moreover, we show how geographic basis risk inherent to weather derivatives can be mitigated by regional diversification. 

  • 5.
    Elnaggar, Mohamed
    et al.
    Department of Engineering, Palestine Technical College, Gaza Strip, Palestine.
    Edwan, Ezzaldeen
    Department of Engineering, Palestine Technical College, Gaza Strip, Palestine.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Wind energy potential of Gaza using small wind turbines: A feasibility study2017In: Energies, E-ISSN 1996-1073, Vol. 10, no 8, article id 1229Article in journal (Refereed)
    Abstract [en]

    In this paper, we conduct a feasibility study of the wind energy potential in Gaza, which suffers from a severe shortage of energy supplies. Our calculated energy harvested from the wind is based on data for a typical meteorological year, which are fed into a small wind turbine of 5 kW power rating installable on the roof of residential buildings. The expected annual energy output at a height of 10 m amounts to 2695 kWh, but it can be increased by 35-125% at higher altitudes between 20 m and 70 m. The results also depict the great potential of wind energy to complement other renewable resources such as solar energy: The harvested energy of a wind system constitutes to up to 84% of the annual output of an equivalent power rating photovoltaic system and even outperforms the solar energy in the winter months. We also show that one wind turbine and one comparable photovoltaic system together could provide enough energy for 3.7 households. Hence, a combination of wind and solar energy could stabilize the decentralized energy production in Gaza. This is very important in a region where people seek to reach energy self-sufficient buildings due to the severe electricity shortage in the local grid.

  • 6.
    Grau, Aaron
    et al.
    Humboldt-Universität zu Berlin, Department für Agrarökonomie, Berlin, Deutschland.
    Jasic, Svetlana
    Humboldt-Universität zu Berlin, Department für Agrarökonomie, Berlin, Deutschland.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Department für Agrarökonomie, Berlin, Deutschland.
    Odening, Martin
    Humboldt-Universität zu Berlin, Department für Agrarökonomie, Berlin, Deutschland.
    The impact of production intensity on agricultural land prices2019In: Journal of the Austrian Society of Agricultural Economics, ISSN 1815-1027, Vol. 29, p. 61-67Article in journal (Refereed)
    Abstract [en]

    This paper is one of the first attempts to utilize the theoretical framework of the new economic geography for explaining agricultural land prices. We adopt a model proposed by Pflüger and Tabuchi (2010), which allows to consider land as a production factor. We derive a short-run equilibrium that relates land rental prices to production intensity. The latter is measured as labor intensity, i.e., the ratio of labor cost and land used for agricultural production and additionally by livestock density. The model is applied to the agricultural sector in West Germany using county level price and cost data of the FADN. A spatial lag model clearly rejects the null hypothesis of no impact of labor and livestock intensity on land rental prices.

  • 7.
    Grau, Aaron
    et al.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Jasic, Svetlana
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Odening, Martin
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    The Impact of Production Intensity on Agricultural Land Prices2019Report (Other academic)
    Abstract [en]

    This paper is one of the first attempts to utilize the theoretical framework of the new economic geography for explaining agricultural land prices. We adopt a model proposed by Pflüger and Tabuchi (2010), which allows to consider land as a production factor. We derive a short-run equilibrium that relates land rental prices to production intensity. The latter is measured as labor intensity, i.e., the ratio of labor cost and land used for agricultural production and additionally by livestock density. The model is applied to the agricultural sector in West Germany using county level price and cost data of the FADN. A spatial lag model clearly rejects the null hypothesis of no impact of labor and livestock intensity on land rental prices.

  • 8.
    Grau, Aaron
    et al.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Odening, Martin
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Land price diffusion across borders: The case of Germany2018Report (Other academic)
    Abstract [en]

    Land market regulations are often justified by the assumption that activities of foreign and non-agricultural investors drive up land prices in countries with low land price levels. However, empirical knowledge about the dynamics of agricultural land prices across borders is sparse. Using theGerman reunification as a natural experiment, we study the effect of the former inner German border on the dynamics of agricultural land prices in East and West Germany. We apply a land price diffusion model with an error correction specification that estimates to what extent agricultural land markets are spatially integrated. A novel feature of our model is its ability to distinguish price diffusion within states and across state borders. We find that local agricultural land markets in Germany are linked by a long-run equilibrium relationship. Spatial market integration, however, does not hold among all counties in our study area. Regarding our main research question, we provide evidence for a persistent border effect given that the fraction of spatially integrated counties is larger within states than across the former border. Moreover, we observe non-significant error correction terms for many counties along the former border. From a policy perspective, it is striking to realize that even 25 years after German reunification, pronounced land price differences persist. It is quite likely that price diffusion through existing borders within the EU would take even more time given language barriers, different administrative procedures for land acquisitions, different tax systems, and information asymmetries between domestic and foreign market participants.

  • 9.
    Grau, Aaron
    et al.
    Faculty of Life Sciences, Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Odening, Martin
    Faculty of Life Sciences, Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Ritter, Matthias
    Faculty of Life Sciences, Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Land price diffusion across borders–the case of Germany2020In: Applied Economics, ISSN 0003-6846, E-ISSN 1466-4283, Vol. 52, no 50, p. 5446-5463Article in journal (Refereed)
    Abstract [en]

    Land market regulations are often justified by the assumption that activities of foreign and non-agricultural investors drive up prices in domestic land markets. However, empirical knowledge about the dynamics of agricultural land prices across borders is sparse. Using the German reunification as a natural experiment, we study the effect of the former inner German border on the dynamics of agricultural land prices in East and West Germany. We apply a land price diffusion model with an error correction specification to analyse spatial agricultural land markets. A novel feature of our model is its ability to distinguish price diffusion within states and across state borders. We provide evidence for a persistent border effect given that the fraction of spatially integrated counties is larger within states than across the former border. Moreover, we observe non-significant error correction terms for many counties along the former border. From a policy perspective, it is striking to realize that even 25 years after German reunification, pronounced land price differences persist. It is quite likely that price diffusion through existing borders within the EU would take even more time given language barriers, different institutional frameworks, and information asymmetries between domestic and foreign market participants.

  • 10.
    Helbing, Georg
    et al.
    Department of Agricultural Economics, Humboldt Universität zu Berlin, Berlin, Germany.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt Universität zu Berlin, Berlin, Germany.
    Deep Learning for fault detection in wind turbines2018In: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 98, p. 189-198Article in journal (Refereed)
    Abstract [en]

    Condition monitoring in wind turbines aims at detecting incipient faults at an early stage to improve maintenance. Artificial neural networks are a tool from machine learning that is frequently used for this purpose. Deep Learning is a machine learning paradigm based on deep neural networks that has shown great success at various applications over recent years. In this paper, we review unsupervised and supervised applications of artificial neural networks and in particular of Deep Learning to condition monitoring in wind turbines. We find that – despite a promising performance of supervised methods – unsupervised approaches are prevalent in the literature. To explain this phenomenon, we discuss a range of issues related to obtaining labelled data sets for supervised training, namely quality and access as well as labelling and class imbalance of operational data. Furthermore, we find that the application of Deep Learning to SCADA data is impeded by their relatively low dimensionality, and we suggest ways of working with higher-dimensional SCADA data. 

  • 11.
    Helbing, Georg
    et al.
    Department of Agricultural Economics, Humboldt Universität zu Berlin, Berlin, Germany.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt Universität zu Berlin, Berlin, Germany.
    Improving wind turbine power curve monitoring with standardisation2020In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 145, p. 1040-1048Article in journal (Refereed)
    Abstract [en]

    Against the background of increasing cost pressure, condition monitoring is becoming increasingly relevant to the wind energy industry. The present study examines the role of wind turbulence and the non-constant variance of residuals in power curve monitoring. Power curve monitoring methods are classified and compared by means of Monte Carlo simulations. It is found that adjusting for the non-constant variance of residuals using standardisation may considerably improve the performance of control charts, no matter what method is used to generate them. Additionally, turbulence is found to be an important factor, and including it may further increase the performance of control charts. 

  • 12.
    Helbing, Georg
    et al.
    Department of Agricultural Economics, Humboldt-Universitt zu Berlin, Berlin, Germany.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt-Universitt zu Berlin, Berlin, Germany.
    Power curve monitoring with flexible EWMA control charts2017In: Proceedings - 2017 International Conference on Promising Electronic Technologies, ICPET 2017, IEEE, 2017, p. 124-128Conference paper (Refereed)
    Abstract [en]

    EWMA control charts have been used by several authors to monitor residuals of power curves for fault detection in wind turbines. In this study, we analyze the effect of non-constant variance in the residuals of a power curve on the performance of an EWMA control chart. We show that the variance can be modelled as a function of wind speed and use this insight to derive wind speed-adjusted control limits. A subsequent application of this procedure to a real data set spanning 2.5 years and on simulated data shows that it is able to slightly reduce the false alarm rate of the EWMA control chart.

  • 13.
    Helbing, Georg
    et al.
    Humboldt-Universität zu Berlin, Germany.
    Shen, Zhiwei
    Humboldt-Universität zu Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Estimating location values of agricultural land2017In: German Journal of Agricultural Economics (GJAE), ISSN 0002-1121, E-ISSN 0515-6866, Vol. 66, no 3, p. 188-201Article in journal (Refereed)
    Abstract [en]

    "Bodenrichtwerte" reflect the average location value of land plots within a specific area. They constitute an important source of information that contributes to price transparency on land markets. In Germany, "Bodenrichtwerte" are provided by publicly appointed expert groups (Gutachterausschüsse). Using empirical data from Mecklenburg-Western Pomerania between 2013 and 2015, this article examines the relation between "Bodenrichtwerten" and statistically determined location values. It turns out that "Bodenrichtwerte" tend to underestimate location values of arable land by 11.5% on average. This underestimation can be traced back to the pronounced increase of land prices in the observation period. As an alternative to the expert-based determination of location values, we suggest a nonparametric smoothing procedure that rests on the Propagation-Separation Approach. The application of this data-driven procedure achieves an accuracy comparable to that of official "Bodenrichtwerte" at the one-year ahead prediction of location values without the requirement of expert knowledge.

  • 14.
    Helbing, Georg
    et al.
    Humboldt-Universität zu Berlin, Germany.
    Shen, Zhiwei
    Humboldt-Universität zu Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Estimating location values of agricultural land2017Report (Other academic)
    Abstract [en]

    “Bodenrichtwerte” reflect the average location value of land plots within a specific area. They constitute an important source of information that contributes to price transparency on land markets. In Germany, “Bodenrichtwerte” are provided by publicly appointed expert groups (Gutachterausschüsse). Using empirical data from Mecklenburg-Western Pomerania between 2013 and 2015, this article examines the relation between “Bodenrichtwerten” and statistically determined location values. It turns out that “Bodenrichtwerte” tend to underestimate location values of arable land by 11.5 percent on average. This underestimation can be traced back to the pronounced increase of land prices in the observation period. As an alternative to the expert-based determination of location values, we suggest a nonparametric smoothing procedure that rests on the Propagation-Separation Approach. The application of this data-driven procedure achieves an accuracy comparable to that of official “Bodenrichtwerte” at the one-year ahead prediction of location values without the requirement of expert knowledge.

  • 15.
    Härdle, Wolfgang Karl
    et al.
    Department of Economics and Business Administration, Humboldt University.
    López Cabrera, Brenda
    Department of Economics, Humboldt University, Germany.
    Ritter, Matthias
    Department of Agricultural Economics, Farm Management Group, Humboldt University, Germany.
    Forecast-based pricing of weather derivatives2015In: Handbook on The Macroeconomics of Global Warming / [ed] L. Bernard & W. Semmler, Oxford University Press, 2015Chapter in book (Refereed)
    Abstract [en]

    Forecasting based pricing of weather derivatives (WDs) is a new approach in valuation of contingent claims on nontradable underlyings. Standard techniques are based on historical weather data, so that forward-looking information such as meteorological forecasts or the implied market price of risk (MPR) are often not incorporated. We adopt a risk neutral approach that allows the incorporation of meteorological forecasts in the framework of WD pricing. Weather risk premiums (RPs) are implied from either the information MPR gain or the meteorological forecasts. RP size is interesting for investors and issuers of weather contracts to take advantages of geographic diversification, hedging effects and price determinations. Incorporating either the MPR or forecasts outperforms the standard pricing techniques.

  • 16.
    Härdle, Wolfgang Karl
    et al.
    Humboldt-Universität zu Berlin, Germany.
    López-Cabrera, Brenda
    Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Forecast based Pricing of Weather Derivatives2012Report (Other academic)
    Abstract [en]

    Forecasting based pricing of Weather Derivatives (WDs) is a new approach in valuation of contingent claims on nontradable underlyings. Standard techniques are based on historical weather data. Forward-looking information such as meteorological forecasts or the implied market price of risk (MPR) are often not incorporated. We adopt a risk neutral approach (for each location) that allows the incorporation of meteorological forecasts in the framework of WD pricing. We study weather Risk Premiums (RPs) implied from either the information MPR gain or the meteorological forecasts. The size of RPs is interesting for investors and issuers of weather contracts to take advantages of geographic diversification, hedging effects and price determinations. By conducting an empirical analysis to London and Rome WD data traded at the Chicago Mercantile Exchange (CME), we find out that either incorporating the MPR or the forecast outperforms the standard pricing techniques. 

  • 17.
    Hüttel, Silke
    et al.
    Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Esaulov, Viacheslav
    Humboldt-Universität zu Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Is there a Term Structure in Land Lease Rates?2014Report (Other academic)
    Abstract [en]

    This paper applies the concept of a term structure to agricultural land rental prices. Based on theoretical considerations, we develop a hedonic pricing model that allows for different shapes of the term structure curve while controlling for other price-relevant characteristics. We apply this model to land lease contracts in Saxony-Anhalt concluded between 2002 and 2010. We find an upward-sloping term structure at the beginning, that is, market participants expected increasing rental prices. For the subsequent years, however, we detect a single-humped term structure. Hence, market participants revised their expectations and assumed a decline of land rental prices in the long-term.

  • 18.
    Hüttel, Silke
    et al.
    University of Rostock, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Esaulov, Viacheslav
    Humboldt-Universität zu Berlin, Germany.
    Odening, Marting
    Humboldt-Universität zu Berlin, Germany.
    Is there a term structure in land lease rates?2016In: European Review of Agricultural Economics, ISSN 0165-1587, E-ISSN 1464-3618, Vol. 43, no 1, p. 165-187Article in journal (Refereed)
    Abstract [en]

    This article applies the concept of a term structure to agricultural land rental prices. Based on theoretical considerations, we develop a hedonic pricing model that allows for different shapes of the term structure curve while controlling for other price-relevant characteristics. We apply this model to land lease contracts in Saxony-Anhalt. We find an upward-sloping term structure during the agricultural price boom in 2007 and 2008, where market participants expected increasing rental prices. For the subsequent years, however, we detect a single-humped term structure. Hence, market participants revised their expectations and assumed a decline of land rental prices in the long term. 

  • 19.
    Kionka, Marlene
    et al.
    Faculty of Life Sciences, Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Musshoff, Oliver
    Department of Agricultural Economics and Rural Development, Georg-August-Universität Göttingen, Göttingen, Germany.
    Ritter, Matthias
    Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE). Faculty of Life Sciences, Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Uhlemann, Jan-Philip Rado
    Business Economics Group, Wageningen University, Wageningen, The Netherlands.
    Odening, Martin
    Faculty of Life Sciences, Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Optimal reserve prices for land auctions in Eastern Germany2022In: Applied Economics Letters, ISSN 1350-4851, E-ISSN 1466-4291Article in journal (Refereed)
    Abstract [en]

    Privatization auctions are seen as culprit for rising prices in eastern Germany. This study aims to analyse whether privatization auctions could have earned even higher revenues by setting optimal reserve prices. For this purpose, a structural estimation approach is applied to determine reserve prices and to compare the resulting expected revenues with actual revenues. The data set includes land auctions in eastern Germany from 2005-2019. The empirical results illustrate that room for increasing revenues exists, but reserve prices would be required to be higher than actual land prices. A potential consequence of high reserve prices is the risk of delays in the privatization process.

  • 20.
    Kionka, Marlene
    et al.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Odening, Martin
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Plogmann, Jana
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Measuring Liquidity in Agricultural Land Markets2020Report (Other academic)
    Abstract [en]

    This paper contributes to the sparse empirical literature on measuring liquidity in agricultural landmarkets. Using data from Lower Saxony (Germany), we inspect the spatial and temporal variabilityof various liquidity indicators. We apply a panel vector autoregression (VAR) and Granger causalitytests to examine the relationship between liquidity and prices and to identify further determinantsof land market liquidity, such as supply shocks and clientele effects. Unlike in housing markets, nopositive relationship between prices and market liquidity exists. We conclude that in agriculturalland markets, a high demand from expanding farms absorbs supply shocks regardless of prevailingprices.

  • 21.
    Kionka, Marlene
    et al.
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Odening, Martin
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Plogmann, Jana
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Measuring liquidity in agricultural land markets2022In: Agricultural Finance Review, ISSN 0002-1466, E-ISSN 2041-6326, Vol. 82, no 4, p. 690-713Article in journal (Refereed)
    Abstract [en]

    Purpose: Liquidity is an important aspect of market efficiency. The purpose of this paper is threefold: first, this paper aims to discuss indicators that provide information about liquidity in agricultural land markets. Second, this paper aims to reflect on determinants of market liquidity and analyze the relationship with land prices. Third, this paper aims to conduct an empirical analysis for Germany that illustrates these concepts and allows hypothesis testing.

    Design/methodology/approach: This study reviews liquidity dimensions and measurement in financial markets and derives indicators applicable to farmland markets. In an empirical analysis, this study exhibits the spatial and temporal variability of land market liquidity in Lower Saxony, a German federal state with the highest agricultural production value. This study uses a rich dataset that includes 72,547 sale transactions of arable land between 1990 and 2018. The research focuses on volume-based (number of transactions, volume and turnover) and time-based (trading frequency and durations) measures. A panel vector autoregression and Granger causality tests are applied to investigate the relation between land turnover and land prices.

    Findings: The paper confirms the thinness of farmland markets but also reveals regional and temporal heterogeneity of land market liquidity. This study finds that the relation between market liquidity and prices is ambiguous. This study concludes that a high demand from expanding farms absorbs supply shocks regardless of the current price level in agricultural land markets.

    Originality/value: Even though the relevance of agricultural land markets’ thinness is widely acknowledged in the literature, this paper is one of the first attempts to measure liquidity in agricultural land markets and to explain its relationship with land prices.

  • 22.
    López Cabrera, Brenda
    et al.
    Humboldt-Universität zu Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Pricing Rainfall Derivatives at the CME2013Report (Other academic)
    Abstract [en]

    Many business people such as farmers and financial investors are affected by indirect losses caused by scarce or abundant rainfall. Because of the high potential of insuring rainfall risk, the Chicago Mercantile Exchange (CME) began trading rainfall derivatives in 2011. Compared to temperature derivatives, however, pricing rainfall derivatives is more difficult. In this article, we propose to model rainfall indices via a flexible type of distribution, namely the normal-inverse Gaussian distribution, which captures asymmetries and heavy-tail behaviour. The prices of rainfall futures are computed by employing the Esscher transform, a well-known tool in actuarial science. This approach is flexible enough to price any rainfall contract and to adjust theoretical prices to market prices by using the calibrated market price of risk. This empirical analysis is conducted with U.S. precipitation data and CME futures data providing first results on the market price of risk for rainfall derivatives. 

  • 23.
    López Cabrera, Brenda
    et al.
    Humboldt-Universität zu Berlin, Ladislaus von Bortkiewicz Chair of Statistics, Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Pricing rainfall futures at the CME2013In: Journal of Banking & Finance, ISSN 0378-4266, E-ISSN 1872-6372, Vol. 37, no 11, p. 4286-4298Article in journal (Refereed)
    Abstract [en]

    Many business people such as farmers and financial investors are affected by indirect losses caused by scarce or abundant rainfall. Because of the high potential of insuring rainfall risk, the Chicago Mercantile Exchange (CME) began trading rainfall derivatives in 2011. Compared to temperature derivatives, however, pricing rainfall derivatives is more difficult. In this article, we propose to model rainfall indices via a flexible type of distribution, namely the normal-inverse Gaussian distribution, which captures asymmetries and heavy-tail behaviour. The prices of rainfall futures are computed by employing the Esscher transform, a well-known tool in actuarial science. This approach is flexible enough to price any rainfall contract and to adjust theoretical prices to market prices by using the calibrated market price of risk. The empirical analysis is conducted with US precipitation data and CME futures data providing first results on the market price of risk for rainfall derivatives.

  • 24.
    Mansi, Ghada
    et al.
    Engineering Program Department, Palestine Technical College, Deir El-Balah, Palestine.
    Edwan, Ezzaldeen
    Engineering Program Department, Palestine Technical College, Deir El-Balah, Palestine.
    Elnaggar, Mohamed
    Engineering Program Department, Palestine Technical College, Deir El-Balah, Palestine.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Design of COTS Vertical Axis Wind Turbine for Urban Areas2018In: Proceedings - 2018 International Conference on Promising Electronic Technologies, ICPET 2018, IEEE, 2018, p. 69-73Conference paper (Refereed)
    Abstract [en]

    In this paper we describe the design of a vertical axis wind turbine (VAWT) that fits residential areas. Such turbines are needed in regions with dense population such as Gaza Strip where the majority of the population are living in urban areas and they seek to reach energy self-sufficient buildings due to the severe electricity shortage in the local grid. The main consideration for a VAWT wind turbine to be suitable for urban areas is the safety factor. Another consideration is being able to turn and produce electricity at low wind speeds. Those two factors will shape the design of the VAWT wind turbine. The designed wind turbine should be compact enough to be installed on rooftops. A target power rating of 5 k Watt is set for the wind turbine as a considerable amount of power to supply a typical residential home. The efficiency of the designed wind turbine is validated experimentally by the recorded wind speeds from an anemometer and the estimated harvested power from the turbine itself. Further schemes and modifications on the design are suggested for improving the power efficiency.

  • 25.
    Myrna, Olena
    et al.
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Odening, Martin
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    The influence of wind energy and biogas on farmland prices2019In: Land, E-ISSN 2073-445X, Vol. 8, no 1, article id 19Article in journal (Refereed)
    Abstract [en]

    In the context of the rapid development of renewable energy in Germany in the last decade, and increased concerns regarding its potential impacts on farmland prices, this paper investigates the impact of wind energy and biogas production on agricultural land purchasing prices. To quantify the possible impact of the cumulative capacity of wind turbines and biogas plants on arable land prices in Saxony-Anhalt, we estimate a community-based and a transaction-based model using spatial econometrics and ordinary least squares. Based on data from 2007 to 2016, our analysis shows that a higher cumulative capacity of wind turbines in communities leads to higher farmland transaction prices, though the effect is very small: if the average cumulative capacity of wind turbines per community doubles, we expect that farmland prices per hectare increase by 0.4%. Plots that are directly affected by a wind turbine or part of a regional development plan, however, experience strong price increases.

  • 26.
    Odening, Martin
    et al.
    Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, Department für Agrarökonomie, Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, Department für Agrarökonomie, Berlin, Germany.
    Hüttel, Silke
    Universität Rostock, Faculty of Agricultural and Environmental Sciences, Chair of Agricultural Economics, Rostock, Germany.
    The term structure of land lease rates2015Conference paper (Refereed)
    Abstract [en]

    This paper applies the concept of a term structure to agricultural land rental prices. Based on theoretical considerations, we develop a hedonic pricing model that allows for different shapes of the term structure curve while controlling for other price-relevant characteristics. We apply this model to land lease contracts in Saxony-Anhalt concluded between 2002 and 2010. We find an upward-sloping term structure at the beginning, that is, market participants expected increasing rental prices. For the subsequent years, however, we detect a single-humped term structure. Hence, market participants revised their expectations and assumed a decline of land rental prices in the long-term.

  • 27.
    Odening, Martin
    et al.
    Department for Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Ritter, Matthias
    Department of Agricultural Economics, Humboldt-Universitt zu Berlin, Berlin, Germany.
    Yang, Xinyue
    Department for Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Agricultural Land Prices and the Law of One Price2016In: Proceedings of the 26th Annual Conference of the Austrian Society of Agricultural Economics Wien, 15-16 September 2016, 2016, p. 11-12Conference paper (Refereed)
    Abstract [en]

    The focus of this paper is on spatial market integration in agricultural land markets. We scrutinize the applicability of the law of one price to land markets while distinguishing between absolute and relative versions of this “law”. Panel data unit root and stationarity tests are applied to land sale prices in the German state Lower Saxony where we detect three main clusters with different price developments. Our results indicate that the law of one price holds only locally due to structural differences among regions.

  • 28.
    Pieralli, Simone
    et al.
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Efficiency of wind power production and its determinants2015In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 90, p. 429-438Article in journal (Refereed)
    Abstract [en]

    This article examines the efficiency of wind energy production. Using non-convex efficiency analysis, we quantify production losses for 19 wind turbines in four wind parks across Germany. In a second stage regression, we adapt the linear regression results of Kneip, Simar, and Wilson (2015) to explain electricity losses by means of a bias-corrected truncated regression analysis. The results show that electricity losses amount to 27% of the maximal producible electricity. Most of these losses are from changing wind conditions, while 6% are from turbine errors.

  • 29.
    Pieralli, Simone
    et al.
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Efficiency of Wind Power Production and its Determinants2015Conference paper (Refereed)
    Abstract [en]

    This article examines the efficiency of wind energy production. Using non-convex efficiency analysis, we quantify production losses for 19 wind turbines in four wind parks across Germany. In a second stage regression, we adapt the linear regression results of Kneip, Simar, and Wilson (2014) to explain electricity losses by means of a bias-corrected truncated regression analysis. The results show that electricity losses amount to 27% of the maximal producible electricity. Most of these losses are from changing wind conditions, while 6% are from turbine errors.

  • 30.
    Pieralli, Simone
    et al.
    Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Efficiency of Wind Power Production and its Determinants2015Report (Other academic)
    Abstract [en]

    This article examines the efficiency of wind energy production. We quantify production losses in four wind parks across Germany for 19 wind turbines with non-convex efficiency analysis. In a second stage regression, we adapt the linear regression results of Kneip, Simar, Wilson (2014) to explain electricity losses by means of a bias-corrected truncated regression. Our results show that electricity losses amount to 27% of the maximal producible electricity. These losses can be mainly traced back to changing wind conditions while only 6 % are caused by turbine errors.

  • 31.
    Plogmann, J.
    et al.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Unter den Linden 6, Berlin, D-10099, Germany.
    Mußhoff, O.
    Georg-August-Universität Göttingen, Department of Agricultural Economics and Rural Development, Platz der Göttinger Sieben 5, Göttingen, D-37073, Germany.
    Odening, M.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Unter den Linden 6, Berlin, D-10099, Germany.
    Ritter, Matthias
    Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Farm growth and land concentration2022In: Land use policy, ISSN 0264-8377, E-ISSN 1873-5754, Vol. 115, article id 106036Article in journal (Refereed)
    Abstract [en]

    Structural change in agriculture is characterized by the interdependency of farms’ growth decisions due to the scarcity of agricultural land. This paper adds to the sparse empirical literature on the relation between land market concentration and farm size changes, considering different definitions of the relevant market. Using data from the Integrated Administrative Control System (IACS) from 2005 until 2017 for Brandenburg, Germany, we find that about half of the land transactions occur beyond municipality borders. This emphasizes the importance of carefully defining the relevant market. The descriptive analysis shows that although concentration rates, on average, did not increase over time, spatial differences are present. In the econometric analysis, we apply a two-stage model to analyze how competition for agricultural land impacts the probability and relative level of expansion. For farms that remained active between 2005 and 2017, we find a negative relation between farm size and relative growth. Our conjecture that higher inequality of land distribution fosters the expansion of large farms was not confirmed.

  • 32.
    Plogmann, J.
    et al.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Unter Den Linden 6, Berlin, 10099, Germany.
    Mußhoff, O.
    Georg-August-Universität Göttingen, Department of Agricultural Economics and Rural Development, Platz der Göttinger Sieben 5, Göttingen, Göttingen, 37073, Germany.
    Odening, M.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Unter Den Linden 6, Berlin, 10099, Germany.
    Ritter, Matthias
    Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE). Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Unter Den Linden 6, Berlin, 10099, Germany.
    Farmland sales under returns and price uncertainty2022In: Economic Modelling, ISSN 0264-9993, E-ISSN 1873-6122, Vol. 117, article id 106044Article in journal (Refereed)
    Abstract [en]

    This paper investigates the observed heterogeneity in the liquidity of agricultural land markets. We adopt a real options model to determine the value of an opportunity to sell farmland and derive the optimal disinvestment triggers. A proportional hazards model is applied to estimate the duration between land sales in Germany and test the implications of the real options model. In contrast to expectations, we find an ambiguous effect of returns and price volatility on the optimal timing of land sales. There is no evidence that non-agricultural investors buy and sell land more frequently than farmers. Our results contribute to the current discussion on land market regulations, one major point of which is capping land prices. According to our results, such policies could increase the rent–price ratio and thus discourage land sales. In turn, the land supply would be reduced, causing further price pressure on farmland markets.

  • 33.
    Plogmann, Jana
    et al.
    Georg-August-Universität Göttingen, Department of Agricultural Economics and Rural Development; Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Mußhoff, Oliver
    Georg-August-Universität Göttingen, Department of Agricultural Economics and Rural Development, Göttingen.
    Odening, Martin
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Farm Growth and Land Concentration2020Report (Other academic)
    Abstract [en]

    Structural change in agriculture is characterized by the interdependency of farms’ growth decisions due to the limited availability of the production factor land. This paper adds to the sparse empirical literature on the relation between land market concentration and farm size changes, considering different definitions of the relevant market. Using data from the Integrated Administrative Control System (IACS) from 2005 until 2017 for Brandenburg, Germany, we find that about half of the land transactions occur beyond municipality borders. This emphasizes the importance of carefully defining the relevant market. The descriptive analysis shows that although concentration rates, on average, did not increase over time, spatial differences are present. In the econometric analysis, we apply a two-stage model to analyze how competition for agricultural land impacts the probability and level of expansion. It shows that for farms that remained active between 2005 and 2017, farms that defragment are less likely to expand. Moreover, we find that the expansion behavior between groups of small and large farms differs with increasing inequality. One potential reason for this might be the existence of market power in land markets.

  • 34.
    Plogmann, Jana
    et al.
    Georg-August-Universität Göttingen, Humboldt-Universität zu Berlin, Germany.
    Mußhoff, Oliver
    Georg-August-Universität Göttingen, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    What Moves the German Land Market?: A Decomposition of the Land Rent-Price Ratio2020In: German Journal of Agricultural Economics (GJAE), ISSN 0002-1121, E-ISSN 0515-6866, Vol. 69, no 1, p. 1-18Article in journal (Refereed)
    Abstract [en]

    The price increases on agricultural land markets over the last decade have triggered a debate about land as an attractive investment opportunity for agricultural and non-agricultural investors. In a static environment, the rent-price ratio provides a first indicator of the profitability of an investment in land. In this paper, we apply the dynamic Gordon growth model to Western Germany and decompose the rent-price ratio into the expected present values of rental growth rates, real interest rates, and a land premium, i.e., the excess return on investment. This analysis reveals that the recent price surge on agricultural land markets was not unprecedented; that the land market rent-price ratio is rather low and varies considerably among federal states; and that (expected) premia for land are mostly negative. Finally, we find that changing expected present values of returns on land investments are the major driver for land price volatility.

  • 35.
    Plogmann, Jana
    et al.
    Georg-August-Universität Göttingen, Department of Agricultural Economics and Rural Development; Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Mußhoff, Oliver
    Georg-August-Universität Göttingen, Department of Agricultural Economics and Rural Development, Göttingen.
    Odening, Martin
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    What Moves the German Land Market? A Decomposition of the Land Rent-Price Ratio2018Report (Other academic)
    Abstract [en]

    The price increases on agricultural land markets in the last decade have triggered a debate about land as an attractive investment opportunity for agricultural and non-agricultural investors. In a static environment, the rent-price ratio provides a first indicator of the profitability of an investment in land. In this paper, we apply the dynamic Gordon growth model to Western Germany and decompose the rent-price ratio into the expected present values of rental growth rates, real interest rates, and a land premium, i.e., the excess return on investment. This analysis reveals that the recent price surge on agricultural land markets was not unprecedented; that the land market rent-price ratio is rather low compared to other markets and varies considerably among federal states; and that (expected) premia for land are mostly negative, rendering investments in farmland unprofitable for financial investors. Finally, we find that changing expected present values of returns on land investments are the major driver for land price volatility.

  • 36.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Germany.
    Can the market forecast the weather better than meteorologists?2012Report (Other academic)
    Abstract [en]

    Many companies depend on weather conditions, so they require reliable weather forecasts for production planning or risk hedging. In this article, we propose a new way of gaining weather forecasts by exploiting the forward-looking information included in the market prices of weather derivatives traded at the Chicago Mercantile Exchange (CME). For this purpose, the CME futures prices of two monthly temperature indices relevant for the energy sector are compared with index forecasts derived from meteorological temperature forecasts. It turns out that the market prices generally outperform the meteorological forecasts in predicting the outcome of the monthly index. Hence, companies whose profit strongly depends on these indices, such as energy companies, can profit from this additional information source about future weather.

  • 37.
    Ritter, Matthias
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Weather forecasting with market prices of weather futures2013In: Journal of Energy Markets, ISSN 1756-3607, E-ISSN 1756-3615, Vol. 6, no 4, p. 25-41Article in journal (Refereed)
    Abstract [en]

    Many companies depend on weather conditions, so they require reliable weather forecasts for production planning or risk hedging. In this paper, we propose a new way of obtaining weather forecasts by exploiting the forward-looking information included in the market prices of weather derivatives traded at the Chicago Mercantile Exchange (CME). For this purpose, the CME futures prices of two monthly temperature indexes relevant for the energy sector are compared with index forecasts derived from meteorological temperature forecasts. It turns out that the market prices generally outperform the meteorological forecasts in predicting the outcome of the monthly index. Hence, companies whose profit strongly depends on these indexes, such as energy companies, can profit from this additional information source about future weather.

  • 38.
    Ritter, Matthias
    et al.
    Humboldt-Universität zu Berlin, Department of Agricultural Economics, Berlin, Germany.
    Deckert, Lars
    4initia GmbH, Berlin, Germany.
    Site assessment, turbine selection, and local feed-in tariffs through the wind energy index2017In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 185, p. 1087-1099Article in journal (Refereed)
    Abstract [en]

    Since wind energy is rapidly growing, new wind farms are installed worldwide and a discussion is going on concerning the optimal political framework to promote this development. In this paper, we present a wind energy index, which is supportive for wind farm planners, operators, and policy-makers. Based on long-term and low-scale reanalysis wind speed data from MERRA and true production data, it can predict the expected wind energy production for every location and turbine type. After an in-sample and out-of-sample evaluation of the index performance, it is applied to assess the wind energy potential of locations in Germany, to compare different turbine types, and to derive the required compensation in terms of locally different feed-in tariffs. We show that in many parts of South Germany, profitability of new wind farms cannot be achieved given the current legal situation. 

  • 39.
    Ritter, Matthias
    et al.
    Humboldt-Universität zu Berlin, Germany.
    Deckert, Lars
    4initia GmbH, Germany.
    Site assessment, turbine selection, and local feed-in tariffs through the wind energy index2015Report (Other academic)
    Abstract [en]

    Since wind energy is rapidly growing, new wind farms are installed world-wide and a discussion is going on concerning the optimal political framework to promote this development. In this paper, we present a wind energy index, which is supportive for wind park planners, operators, and policy-makers. Based on long-term and low-scale reanalysis wind speed data from MERRA and true production data, it can predict the expected wind energy production for every location and turbine type. After an in-sample and out-of-sample evaluation of the index performance, it is applied to assess the wind energy potential of locations in Germany, to compare different turbine types and to derive the required compensation in terms of locally different feed-in tariffs. We show that in many parts of South Germany, profitability of new wind parks cannot be achieved given the current legal situation.

  • 40.
    Ritter, Matthias
    et al.
    Jönköping University, Jönköping International Business School, JIBS, Economics. Jönköping University, Jönköping International Business School, JIBS, Centre for Entrepreneurship and Spatial Economics (CEnSE).
    Djabarian, Yasmin
    Hsch Forum Digitalisierung, Stifterverband, Pariser Pl, D-10117 Berlin, Germany..
    Grosse, Maria
    Humboldt Univ, Zentralinst Profess Sch Educ, Unter Linden 6, D-10099 Berlin, Germany..
    Holm-Mueller, Karin
    Univ Bonn, Inst Lebensmittel & Ressourcenokonom, Nussallee 21, D-53115 Bonn, Germany..
    Leonhardt, Heidi
    Univ Bodenkultur Wien, Dept Wirtschafts & Sozialwissensch, Inst Nachhaltige Wirtschaftsentwicklung, Feistmantelstr 4, A-1180 Vienna, Austria..
    Uhlemann, Jan-Philip
    Wageningen Univ, Business Econ Grp, Hollandseweg 1, NL-6706 KN Wageningen, Netherlands..
    Digitale Lehre – was bleibt? Die Lehren aus den Digitalsemestern für die Hochschullehre in den Wirtschaftsund Sozialwissenschaften des Landbaus [Digital Teaching - what remains? The Lessons from the Digital Semesters for University Teaching in the Economic and Social Sciences of Agriculture]2022In: Berichte über Landwirtschaft, ISSN 0005-9080, Vol. 100, no 1, p. 1-22Article in journal (Refereed)
    Abstract [en]

    The spontaneous conversion of university teaching to digital teaching in the summer semester of 2020 due to the Corona pandemic provided a digitalization boost to German universities. After much experience and a gradual return to on-campus teaching, it is time to consider how a meaningful combination of on-campus and digital teaching might look like after the end of the Corona pandemic. This article presents various student and lecturer experiences and lessons learned and their plans for future teaching. It also discusses in more detail the conceptual implementation of blended learning, the benefits and challenges of digital tools, and digital exams. Many opportunities emerge to retain elements of digital teaching in on-campus teaching. This requires support from the universities and an increased exchange among teachers.

  • 41.
    Ritter, Matthias
    et al.
    Department of Agricultural Economics, Humboldt-Universitt zu Berlin, Berlin, Germany.
    Helbing, Georg
    Department of Agricultural Economics, Humboldt-Universitt zu Berlin, Berlin, Germany.
    Shen, Zhiwei
    Department for Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Odening, Martin
    Department for Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Estimating location values of agricultural land2017Conference paper (Refereed)
    Abstract [en]

    “Bodenrichtwerte” reflect the average location value of land plots within a specific area. They constitute an important source of information that contributes to price transparency on land markets. In Germany, “Bodenrichtwerte” are provided by publicly appointed expert groups (Gutachterausschüsse). Using empirical data from Mecklenburg-Western Pomerania between 2013 and 2015, this article examines the relation between “Bodenrichtwerten” and statistically determined location values. It turns out that “Bodenrichtwerte” tend to underestimate location values of arable land by 11.5 percent on average. This underestimation can be traced back to the pronounced increase of land prices in the observation period. As an alternative to the expert-based determination of location values, we suggest a nonparametric smoothing procedure that rests on the Propagation-Separation Approach. The application of this data-driven procedure achieves an accuracy comparable to that of official “Bodenrichtwerte” at the one-year ahead prediction of location values without the requirement of expert knowledge.

  • 42.
    Ritter, Matthias
    et al.
    Humboldt-Universität zu Berlin.
    Hüttel, Silke
    Universität Rostock.
    Windenergie: Preistreiber auf dem Bodenmarkt?2016In: Vermessung Brandenburg: Nr. 1/2016 / [ed] S. Frey, A. Schönitz & S. Wagenknecht, Potsdam: Landesvermessung und Geobasisinformation Brandenburg , 2016, , p. 25p. 25-31Chapter in book (Other academic)
    Abstract [de]

    Die Bodenpreise sind in den letzten Jahren in ganz Deutschland stark angestiegen. Als mögliche Ursachen werden dieverbesserte Ertragslage, das Engagement außerlandwirtschaftlicher Investoren oder die Förderung der Biogasnutzung diskutiert. Zur gleichen Zeit wurdejedoch auch der Ausbau der Windenergienutzung im Rahmen des ErneuerbareEnergien Gesetzes stark gefördert. Aktuell ist das Land Brandenburg der zweitgrößte Produzent von Windenergie anLand in Deutschland. In diesem Beitraguntersuchen wir, inwieweit sich die Förderung der Windenergienutzung in landwirtschaftlichen Bodenpreisen in Brandenburg kapitalisiert.

  • 43.
    Ritter, Matthias
    et al.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Hüttel, Silke
    Odening, Martin
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Department of Agricultural Economics, Berlin.
    Seifert, Stefan
    Revisiting the relationship between land price and parcel size2019Report (Other academic)
    Abstract [en]

    Hedonic land price models often use parcel size as an explanatory variable. Empirical analyses, however, are rather ambiguous regarding the direction and the size of the effect of this variable on farmland values. The objective of this paper is to investigate this size-price relation in detail and to derive recommendations for an appropriate specification of hedonic land price models. Our analysis consists of three steps. First, we conduct a meta-analysis based on a comprehensive literature review. Second, we analyze a dataset of more than 80,000 land transactions in Saxony-Anhalt, Germany, using the non-parametric locally weighted scatterplot smoothing (LOWESS) estimator. This unconditional smoothing algorithm identifies negative size-price relations for very small and large plots, whereas it finds a positive relation for medium plot. We use this finding in our third step, a hedonic land price model, in which the size-price relation is modelled conditional on land and buyer characteristics. From these steps, we conclude that the complex relationship between land price and plot size cannot be captured by a simple functional form since it is affected by several economic factors, such as economies of size, transaction cost, and financial constraints. 

  • 44.
    Ritter, Matthias
    et al.
    Department of Agricultural Economics, Humboldt-Universität zu Berlin,Berlin, Germany.
    Hüttel, Silke
    Institute of Food and Resource Economics, University of Bonn, Bonn, Germany.
    Odening, Martin
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Seifert, Stefan
    Institute of Food and Resource Economics, University of Bonn, Bonn, Germany.
    Revisiting the relationship between land price and parcel size in agriculture2020In: Land use policy, ISSN 0264-8377, E-ISSN 1873-5754, Vol. 97, article id 104771Article in journal (Refereed)
    Abstract [en]

    Hedonic land price models often use parcel size as an explanatory variable. Empirical analyses, however, are rather ambiguous regarding the direction and the size of the effect of this variable on farmland values. The objective of this paper is to investigate this size–price relation for agricultural land use in detail and to derive recommendations for an appropriate specification of hedonic land price models. Our analysis consists of three steps. First, we conduct a meta-analysis based on a comprehensive literature review. Second, we analyze a dataset of more than 80,000 agricultural land transactions in Saxony-Anhalt, Germany, using the nonparametric locally weighted scatterplot smoothing (LOWESS) estimator. This unconditional smoothing algorithm identifies negative size–price relations for very small and large plots, whereas it finds a positive relation for medium plots. We use this finding in our third step, a hedonic land price model, in which the size–price relation is modeled conditional on land and buyer characteristics. From these steps, we conclude that the complex relationship between land price and plot size cannot be captured by a simple functional form since it is affected by several economic factors, such as economies of size, transaction costs, and financial constraints.

  • 45.
    Ritter, Matthias
    et al.
    Department für Agrarökonomie, Humboldt-Universität zu Berlin, Berlin.
    Hüttel, Silke
    Universität Rostock, Rostock.
    Walter, Marian
    Department für Agrarökonomie, Humboldt-Universität zu Berlin, Berlin.
    Odening, Martin
    Department für Agrarökonomie, Humboldt-Universität zu Berlin, Berlin.
    Der Einfluss von Windkraftanlagen auf landwirtschaftliche Bodenpreise [The influence of wind energy on agricultural land prices]2015In: Berichte über Landwirtschaft, ISSN 0005-9080, Vol. 93, no 3Article in journal (Refereed)
    Abstract [en]

    This study sets out to analyze the trend in farmland prices in one of the eastern states of Germany, Brandenburg, between the years 2000 and 2010. Apart from the usual price determinants, we consider especially the influence of wind power generation. Based on regression analysis, we find a significant positive correlation between the scope of the wind energy and the level of the purchasing prices. The effects are also broken down into a stock, extension and potential effect. It is shown that, on average, the use of wind energy in Brandenburg led to an increase of farmland prices of about five percent, although this effect has regional differences depending on the local wind turbine density.

  • 46.
    Ritter, Matthias
    et al.
    Universität Göttingen, Humboldt- Universität zu Berlin, Collaborative Research Center (CRC), Berlin, Germany.
    Musshoff, Oliver
    Universität Göttingen, Göttingen, Germany.
    Odening, Martin
    Universität Göttingen, Humboldt- Universität zu Berlin, Collaborative Research Center (CRC), Berlin, Germany.
    Meteorological forecasts and the pricing of temperature futures2011In: Journal of Derivatives, ISSN 1074-1240, E-ISSN 2168-8524, Vol. 19, no 2, p. 45-60Article in journal (Refereed)
    Abstract [en]

    In usual pricing approaches for weather derivatives, forward-looking information such as meteorological weather forecasts is not considered. Thus, important knowledge used by market participants is ignored in theory. By extending a standard model for the daily temperature, this article allows the incorpo-ration of meteorological forecasts in the framework of weather derivative pricing and is able to esti-mate the information gain compared with a bench-mark model without meteorological forecasts. This approach is applied for temperature futures referring to New York, Minneapolis, and Cincinnati with meteorological forecast data 13 days in advance. Despite this relatively short forecast horizon, the models using meteorological forecasts outperform the classical approach and more accurately forecast the market prices of the temperature futures traded at the Chicago Mercantile Exchange (CME). Moreover, a concentration on the last two months or on days with actual trading improves the results, whereas an inclusion of hypothetical perfect forecasts worsens them.

  • 47.
    Ritter, Matthias
    et al.
    Department of Agricultural Economics and Rural Development, Georg-August Universität Göttingen, Göttingen, Germany; Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Mußhoff, O.
    Department of Agricultural Economics and Rural Development, Georg-August Universität Göttingen, Göttingen, Germany.
    Odening, Martin
    Department of Agricultural Economics, Humboldt-Universität zu Berlin, Berlin, Germany.
    Minimizing Geographical Basis Using A Multi-Site Rainfall Model2014In: Computational Economics, ISSN 0927-7099, E-ISSN 1572-9974, Vol. 44, no 1, p. 67-86Article in journal (Refereed)
    Abstract [en]

    It is well known that the hedging effectiveness of weather derivatives is interfered by the existence of geographical basis risk, i.e., the deviation of weather conditions at different locations. In this paper, we explore how geographical basis risk of rainfall based derivatives can be reduced by regional diversification. Minimizing geographical basis risk requires knowledge of the joint distribution of rainfall at different locations. For that purpose, we estimate a daily multi-site rainfall model from which optimal portfolio weights are derived. We find that this method allows to reduce geographical basis risk more efficiently than simpler approaches as, for example, inverse distance weighting. 

  • 48.
    Ritter, Matthias
    et al.
    Humboldt-Universität zu Berlin, Germany; Georg-August-Universität Göttingen, Germany.
    Mußhoff, Oliver
    Georg-August-Universität Göttingen, Germany.
    Odening, Martin
    Humboldt-Universität zu Berlin, Germany.
    Meteorological forecasts and the pricing of weather derivatives2010Report (Other academic)
    Abstract [en]

    In usual pricing approaches for weather derivatives, forward-looking information such as meteorological weather forecasts is not considered. Thus, important knowledge used by market participants is ignored in theory. By extending a standard model for the daily temperature, this paper allows the incorporation of meteorological forecasts in the framework of weather derivative pricing and is able to estimate the information gain compared to a benchmark model without meteorological forecasts. This approach is applied for temperature futures referring to New York, Minneapolis and Cincinnati with forecast data 13 days in advance. Despite this relatively short forecast horizon, the models using meteorological forecasts outperform the classical approach and more accurately forecast the market prices of the temperature futures traded at the Chicago Mercantile Exchange (CME). Moreover, a concentration on the last two months or on days with actual trading improves the results. 

  • 49.
    Ritter, Matthias
    et al.
    Department of Agricultural Economics and Rural Development, Georg-August University Göttingen, Göttingen, Germany; Department of Agricultural Economics, Humboldt University Berlin, Berlin, Germany.
    Mußhoff, Oliver
    Department of Agricultural Economics and Rural Development, Georg-August University Göttingen, Göttingen, Germany.
    Odening, Martin
    Department of Agricultural Economics, Humboldt University Berlin, Berlin, Germany.
    Minimizing geographical basis risk of weather derivatives using a multi-site rainfall model2012Conference paper (Refereed)
    Abstract [en]

    Weather risk is one of the main causes for income fluctuation in agriculture. Since 1997, the economic consequences of weather risk can be insured with weather derivatives, which are offered for many different weather events, such as temperature, rainfall, snow or hurricanes. It is well known that the hedging effectiveness of weather derivatives is interfered by the existence of geographical basis risk, i.e., the deviation of weather conditions at different locations. In this paper, we explore how geographical basis risk of rainfall based derivatives can be reduced byregional diversification. Minimizing geographical basis risk requires knowledge of the joint distribution of rainfall at different locations. For that purpose, we estimate a daily multi-site rainfall model from which optimal portfolio weights are derived. We find that this method allows to reduce geographical basis risk more efficiently than simpler approaches as, for example, inverse distance weighting.

  • 50.
    Ritter, Matthias
    et al.
    Humboldt-Universität zu Berlin, Faculty of Life Sciences, Berlin, Germany.
    Ott, Derek V. M.
    Neurology Clinic with Stroke Unit and Early Rehabilitation, Unfallkrankenhaus Berlin, Berlin, Germany.
    Friedemann, Paul
    Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH); Department of Neurology, Experimental and Clinical Research Center; Max Delbrueck Center for Molecular Medicine, Berlin, Germany.
    Haynes, John-Dylan
    Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH); Berlin Center for Advanced Neuroimaging, Bernstein Center for Computational Neuroscience, Berlin, Germany.
    Ritter, Kerstin
    Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health (BIH); Berlin Center for Advanced Neuroimaging, Bernstein Center for Computational Neuroscience, Berlin, Germany.
    COVID-19 – A simple statistical model for predicting intensive care unit load in early phases of the disease2020Report (Other academic)
    Abstract [en]

    One major bottleneck in the ongoing COVID-19 pandemic is the limited number of critical care beds. Due to the dynamic development of infections and the time lag between when patients are infected and when a proportion of them enters an intensive care unit (ICU), the need for future intensive care can easily be underestimated. To infer future ICU load from reported infections, we suggest a simple statistical model that (1) accounts for time lags and (2) allows for making predictions depending on different future growth of infections. We have evaluated our model for three regions, namely Berlin (Germany), Lombardy (Italy), and Madrid (Spain). Before extensive containment measures made an impact, we first estimate the region-specific model parameters. Whereas for Berlin, an ICU rate of 6%, a time lag of 6 days, and an average stay of 12 days in ICU provide the best fit of the data, for Lombardy and Madrid the ICU rate was higher (18% and 15%) and the time lag (0 and 3 days) and the average stay (4 and 8 days) in ICU shorter. The region-specific models are then used to predict future ICU load assuming either a continued exponential phase with varying growth rates (0—15%) or linear growth. Thus, the model can help to predict a potential exceedance of ICU capacity. Although our predictions are based on small data sets and disregard non-stationary dynamics, our model is simple, robust, and can be used in early phases of the disease when data are scarce.

12 1 - 50 of 69
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