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Price volatility of agricultural land in Poland in the context of the European Union

Author

Listed:
  • Bórawski, Piotr
  • Bełdycka-Bórawska, Aneta
  • Szymańska, Elżbieta Jadwiga
  • Jankowski, Krzysztof Józef
  • Dunn, James W.

Abstract

In this paper the price volatility of land in Poland is examined during the years 1992-2016. The analysis concentrates particularly on stationarity, variation and GARCH. Differences in land price changes in particular provinces in Poland are presented and land prices in Poland are compared with other EU countries. The land market in Poland is diverse. Purchasers can buy land from private owners in the market and from the government’s Agricultural Property Agency. Generally, land offered by the Agricultural Property Agency is cheaper, but it is also more difficult to purchase. The authors of the paper used and analyzed quarterly price data from the main Statistical Office in Warsaw in PLN. The survey found high variability for land prices in Poland. The price of agricultural land has increased significantly since the integration of Poland into the EU. In 2016 the average price of land from the (APA) Agricultural Property Agency increased by 791% and the average price of private agricultural land increased by 690.2% in comparison to 2004. The prices of land differ regionally in Poland. In 2016 compared to 2005 the price of land increased the most in Warmińsko-Mazurskie voivodeship (587,2%), Opolskie voivodeship (547,8%) and Lubuskie voivodeship (534,9%). In 2016 in comparison to 2005 the price of agricultural land increased the least in Małopolskie voivodeship (252,6%), Podlaskie voivodeship (295,0%) and Łódzkie voivodeship (304,9%). The study presents the descriptive statistics of agricultural land. The coefficient of variation of price changes in the years 2005-2016 was the highest in Slovakia (69,8%), Romania (60,4%) and Estonia (59,4%) and the lowest in Italy (9,2%) and France (12,1%). The ADF test (Augmented Dickey-Fuller test) shows that the agricultural land prices data can be classified as not stationary. The implication of the GARCH (Generalized Autoregressive Conditional Heteroskedasticity) model of price volatility of agricultural land is that conditional volatility cannot be confirmed.

Suggested Citation

  • Bórawski, Piotr & Bełdycka-Bórawska, Aneta & Szymańska, Elżbieta Jadwiga & Jankowski, Krzysztof Józef & Dunn, James W., 2019. "Price volatility of agricultural land in Poland in the context of the European Union," Land Use Policy, Elsevier, vol. 82(C), pages 486-496.
  • Handle: RePEc:eee:lauspo:v:82:y:2019:i:c:p:486-496
    DOI: 10.1016/j.landusepol.2018.11.027
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    References listed on IDEAS

    as
    1. Zheng Liu & Pengfei Wang & Tao Zha, 2013. "Land‐Price Dynamics and Macroeconomic Fluctuations," Econometrica, Econometric Society, vol. 81(3), pages 1147-1184, May.
    2. Cummings, Ralph Jr. & Rashid, Shahidur & Gulati, Ashok, 2006. "Grain price stabilization experiences in Asia: What have we learned?," Food Policy, Elsevier, vol. 31(4), pages 302-312, August.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    5. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    6. Plantinga, Andrew J. & Lubowski, Ruben N. & Stavins, Robert N., 2002. "The effects of potential land development on agricultural land prices," Journal of Urban Economics, Elsevier, vol. 52(3), pages 561-581, November.
    7. repec:pri:cepsud:91malkiel is not listed on IDEAS
    8. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    9. Bazyli Czyzewski & Radoslaw Trojanek & Anna Matuszczak, 2018. "The Effects of Use Values, Amenities and Payments for Public Goods on Farmland Prices: Evidence from Poland," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 68(1), pages 135-158, March.
    10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    11. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    12. Waszkowski, Adam, 2011. "Hipoteza efektywności rynku; weryfikacja dla indeksu WIG- Spożywczy," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 11(26), pages 1-8, December.
    13. Ihlanfeldt, Keith R., 2007. "The effect of land use regulation on housing and land prices," Journal of Urban Economics, Elsevier, vol. 61(3), pages 420-435, May.
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    4. Kocur-Bera, Katarzyna, 2020. "Understanding information about agricultural land. An evaluation of the extent of data modification in the Land Parcel Identification System for the needs of area-based payments – a case study," Land Use Policy, Elsevier, vol. 94(C).
    5. Balezentis, Tomas & Morkunas, Mangirdas & Volkov, Artiom & Ribasauskiene, Erika & Streimikiene, Dalia, 2021. "Are women neglected in the EU agriculture? Evidence from Lithuanian young farmers," Land Use Policy, Elsevier, vol. 101(C).
    6. Aneta Bełdycka-Bórawska & Piotr Bórawski & Lisa Holden & Tomasz Rokicki & Bogdan Klepacki, 2022. "Factors Shaping Performance of Polish Biodiesel Producers Participating in the Farm Accountancy Data Network in the Context of the Common Agricultural Policy of the European Union," Energies, MDPI, vol. 15(19), pages 1-25, October.
    7. Zhang, Zhihui & Ghazali, Samane & Miceikienė, Astrida & Zejak, Dejan & Choobchian, Shahla & Pietrzykowski, Marcin & Azadi, Hossein, 2023. "Socio-economic impacts of agricultural land conversion: A meta-analysis," Land Use Policy, Elsevier, vol. 132(C).
    8. Zhou Jie & Chai Hua Qi, 2023. "An equilibrium analysis of the impact of real estate price volatility on macroeconomics based on ant colony algorithm," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-26, March.
    9. Mangirdas Morkunas & Povilas Labukas, 2020. "The Evaluation of Negative Factors of Direct Payments under Common Agricultural Policy from a Viewpoint of Sustainability of Rural Regions of the New EU Member States: Evidence from Lithuania," Agriculture, MDPI, vol. 10(6), pages 1-14, June.
    10. Piotr Bórawski & Marta Guth & Aneta Bełdycka-Bórawska & Krzysztof Józef Jankowski & Andrzej Parzonko & James W. Dunn, 2020. "Investments in Polish Agriculture: How Production Factors Shape Conditions for Environmental Protection?," Sustainability, MDPI, vol. 12(19), pages 1-26, October.
    11. Robert BUMBAC, 2019. "Trends and Challenges in Food System Management in Emerging Economies: A Comparative Analysis between Romania and Poland," REVISTA DE MANAGEMENT COMPARAT INTERNATIONAL/REVIEW OF INTERNATIONAL COMPARATIVE MANAGEMENT, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 20(4), pages 491-502, October.
    12. Marks-Bielska, Renata, 2021. "Conditions underlying agricultural land lease in Poland, in the context of the agency theory," Land Use Policy, Elsevier, vol. 102(C).
    13. Andrzej Hornowski & Andrzej Parzonko & Pavel Kotyza & Tomasz Kondraszuk & Piotr Bórawski & Luboš Smutka, 2020. "Factors Determining the Development of Small Farms in Central and Eastern Poland," Sustainability, MDPI, vol. 12(12), pages 1-21, June.

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    More about this item

    Keywords

    price volatility; agricultural land; Poland; EU;
    All these keywords.

    JEL classification:

    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General
    • Q15 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
    • B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Historical; Institutional; Evolutionary; Modern Monetary Theory;

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