A DSGE Model of the Russian Residential Real Estate Market
https://doi.org/10.18288/1994-5124-2024-3-76-117
Abstract
The paper develops a dynamic stochastic general equilibrium (DSGE) model of the Russian economy based on an endogenous housing sector and three categories of homeowners – patient, impatient and non-Ricardian. The DSGE model is applied from the first quarter of 2010 to the fourth quarter of 2019 using a Bayesian method for minimizing the discrepancy between theoretical and empirical impulse responses to a shock due to modified terms of trade. The model is then employed to provide a quantitative assessment of how macro variables respond to shocks generated by the housing market, interest rates, mortgage subsidies, financial liberalization, and altered terms of trade. At the same time, the impact of shocks on a number of economic indicators is largely determined by the functional form of household utility, as demonstrated by the robustness test. The results obtained based on the model also do not demonstrate a strong inertial effect in the economy due to the revival of the residential real estate construction sector, and they contradict a number of studies and expert estimates based primarily on the input-output model. One reason for this discrepancy may be the analysis, which is based on a horizontal supply curve, resulting in an overestimation of the impact of the construction sector on the economy. This DSGE model can serve as a starting point for scenario-based projections of the dynamics of the residential real estate market and the associated mortgage market, for testing the impact of various policy measures on the housing sector, and for assessing their effects on various categories of households.
Keywords
housing market,
mortgage,
IRF matching,
heterogeneous households,
terms of trade,
monetary policy,
fiscal policy,
mortgage subsidies
JEL: E13, E32, E44, F41, H31, R30, R31
Supporting agencies: This study was supported by the Russian Science Foundation’s Grant No 21-78-10020. The author would like to express his gratitude to his supervisor Andrey V. Polbin, Ph.D., Lead Researcher at the Center for Mathematical Modeling of Economic Processes of the IPEI, RANEPA, for valuable insights, comments, and constructive discussions and also to thank the anonymous reviewer for their thorough examination of the text.
About the Author
D. A. Lomonosov
RANEPA
Russian Federation
Russian Federation
Daniil A. Lomonosov, Junior Researcher at the Center for Mathematical Modeling of Economic Processes, Institute of Applied Economic Research
84, k. 2, pr. Vernadskogo, Moscow, 119571,
References
1. Zamnius A. V., Polbin A. V. Otsenka mezhvremennoy elastichnosti zameshcheniya predlozheniya truda dlya zamuzhnikh zhenshchin v Rossii [Estimating Intertemporal Elasticity of Substitution of Labor Supply for Married Women in Russia]. Prikladnaya ekonometrika [Applied Econometrics], 2021, vol. 64, no. 4, pp. 23-48. DOI: 10.22394/1993-7601-2021-64-23-48. (In Russ.)
2. Zamnius A. V., Polbin A. V., Sinelnikov-Murylev S. G. Elastichnost’ predlozheniya truda po zarabotnoy plate u zhenatykh muzhchin v Rossii [The Labor Supply Elasticity for Married Men in Russia]. Ekonomicheskiy zhurnal VShE [HSE Economic Journal], 2022, vol. 26, no. 2, pp. 177-212. DOI: 10.17323/1813-8691-2022-26-2-177-212. (In Russ.)
3. Kuvalin D. B. Pochemu neobkhodimo podderzhivat’ zhilishchnoe stroitel’stvo [Why Is It Necessary to Support Housing Construction?]. Zhilishchnye strategii [Russian Journal of Housing Research], 2021, vol. 8, no. 1, pp. 7-9. DOI: 10.18334/zhs.8.1.112447. (In Russ.)
4. Ovsyannikova T. Yu., Rabtsevich O. V., Yugova I. V. Otsenka mul’tiplikativnogo vliyaniya zhilishchnykh investitsiy na dinamiku gorodskogo razvitiya [Estimating the Multiplier Effect of Housing Investment on the Dynamics of Urban Development]. Zhilishchnye strategii [Russian Journal of Housing Research], 2017, vol. 4, no. 3, pp. 175-192. DOI: 10.18334/zhs.4.3.38584. (In Russ.)
5. Polbin A. V., Sinelnikov-Murylev S. G. Postroenie i kalibrovka DSGE-modeli dlya rossiyskoy ekonomiki s ispol’zovaniem impul’snykh otklikov vektornoy avtoregressii [Developing and Impulse Response Matching Estimation of the DSGE Model for the Russian Economy]. Prikladnaya ekonometrika [Applied Econometrics], 2024, vol. 73, pp. 5-34. DOI: 10.22394/1993-7601-2024-73-5-34. (In Russ.)
6. Roshchina Ya., Ilyunkina N. Analiz vliyaniya mer gosudarstvennoy podderzhki ipotechnogo kreditovaniya na dostupnost’ zhil’ya v Rossii: regional’nyy razrez [Impact of Government Measures to Support Mortgage Lending on Housing Affordability in Russia: Regional Evidence]. Den’gi i kredit [Russian Journal of Money and Finance], 2021, vol. 80, no. 4, pp. 98-123. DOI: 10.31477/rjmf.202104.98. (In Russ.)
7. Shirov A. A., Yantovskiy A. A. Otsenka mul’tiplikativnykh effektov v ekonomike. Vozmozhnosti i ogranicheniya [Assessment of Multiplier Effects in Economics: Features and Limitations]. Vserossiyskiy ekonomicheskiy zhurnal EKO [ECO Russian Economics Journal], 2011, no. 2(440), pp. 40-58. (In Russ.)
8. Shulgin A. Bayesovskaya otsenka DSGE-modeli s dvumya pravilami monetarnoy politiki dlya Rossii. WP12/2014/01 [Bayesian Estimation of the DSGE Model with Two Monetary Policy Rules for Russia. WP12/2014/01]. Moscow, HSE, 2014. (In Russ.)
9. Shulgin A. Skol’ko pravil monetarnoy politiki neobkhodimo pri otsenke DSGE-modeli dlya Rossii? [How Many Monetary Policy Rules Are Needed When Estimating a DSGE Model for Russia?]. Prikladnaya ekonometrika [Applied Econometrics], 2014, no. 4, pp. 3-31. (In Russ.)
10. Adolfsen J. F. Fiscal Tools at the Zero Lower Bound. Copenhagen, Danmarks National Bank, 2017.
11. Aoki K., Proudman J., Vlieghe G. House Prices, Consumption, and Monetary Policy: A Financial Accelerator Approach. Journal of Financial Intermediation, 2004, vol. 13, no. 4, pp. 414-435. DOI: 10.1016/j.jfi.2004.06.003.
12. Ascari G., Castelnuovo E., Rossi L. Calvo vs. Rotemberg in a Trend Inflation World: An Empirical Investigation. Journal of Economic Dynamics and Control, 2011, vol. 35, no. 11, pp. 1852-1867. DOI: 10.1016/j.jedc.2011.06.002.
13. Asimakopoulos P., Asimakopoulos S. Fiscal Policy With Banks and Financial Frictions. Journal of Financial Stability, 2019, vol. 40, pp. 94-109. DOI: 10.1016/j.jfs.2017.10.010.
14. Barsky R. B., House C. L., Kimball M. S. Sticky-Price Models and Durable Goods. American Economic Review, 2007, vol. 97, no. 3, pp. 984-998. DOI: 10.1257/aer.97.3.984.
15. Davis M. A., Heathcote J. Housing and the Business Cycle. International Economic Review, 2005, vol. 46, no. 3, pp. 751-784. DOI: 10.1111/j.1468-2354.2005.00345.x.
16. Diaz-Gimenez J., Prescott C. E., Fitzgerald T., Alvarez F. Banking in Computable General Equilibrium Economies. Journal of Economic Dynamics and Control, 1992, vol. 16, no. 3-4, pp. 533-559. DOI: 10.1016/0165-1889(92)90048-J.
17. Eskelinen M. Monetary Policy, Agent Heterogeneity and Inequality: Insights From a Three-Agent New Keynesian Model. ECB, Working Paper Series no. 2590, 2021. DOI: 10.2866/283105.
18. Fisher I. The Debt-Deflation Theory of Great Depressions. Econometrica, 1933, pp. 337-357. DOI: 0012-9682(193310)1:4<337:TDTOGD>2.0.CO;2-6.
19. Guerrieri L., Iacoviello M. Collateral Constraints and Macroeconomic Asymmetries. Journal of Monetary Economics, 2017, vol. 90, pp. 28-49. DOI: 10.1016/j.jmoneco.2017.06.004.
20. Harding M., Klein M. Monetary Policy and Household Net Worth. Review of Economic Dynamics, 2022, vol. 44, pp. 125-151. DOI: 10.1016/j.red.2021.02.013.
21. Hinterschweiger M., Khairnar K., Ozden T., Stratton T. Macroprudential Policy Interactions in a Sectoral DSGE Model With Staggered Interest Rates. Bank of England Staff Working Paper, no. 904, 2021. DOI: 10.2139/ssrn.3778185.
22. Iacoviello M. House Prices, Borrowing Constraints and Monetary Policy in the Business Cycle. Cambridge, NBER, 2001. https://users.nber.org/~confer/2001/urcf01/iacoviello.pdf.
23. Iacoviello M. House Prices, Borrowing Constraints, and Monetary Policy in the Business Cycle. American Economic Review, 2005, vol. 95, no. 3, pp. 739-764. DOI: 10.1257/0002828054201477.
24. Iacoviello M., Neri S. Housing Market Spillovers: Evidence From an Estimated DSGE Model. American Economic Journal: Macroeconomics, 2010, vol. 2, no. 2, pp. 125-64. DOI: 10.1257/mac.2.2.125
25. Lee J., Song J. Housing and Business Cycles in Korea: A Multi-Sector Bayesian DSGE Approach. Economic Modelling, 2015, vol. 45, pp. 99-108. DOI: 10.1016/j.econmod.2014.11.009.
26. Leung C. Macroeconomics and Housing: А Review of the Literature. Journal of Housing Economics, 2004, vol. 13, no. 4, pp. 249-267. DOI: 10.1016/j.jhe.2004.09.002.
27. Lomonosov D. A. Shocks of Business Activity and Specific Shocks to Oil Market in DSGE Model of Russian Economy and Their Influence Under Different Monetary Policy Regimes. Russian Journal of Money and Finance, 2023, vol. 82, no. 4, pp. 44-79.
28. Mora-Sanguinetti J. S., Rubio M. Recent Reforms in Spanish Housing Markets: An Evaluation Using a DSGE Model. Economic Modelling, 2014, vol. 44, pp. 42-49. DOI: 10.1016/j.econmod.2014.04.028.
29. Nookhwun N., Tsomocos D. Mortgage Default, Financial Disintermediation and Macroprudential Policies. PIER Research Workshop, 2017.
30. Schmitt-Grohé S., Uribe M. Closing Small Open Economy Models. Journal of International Economics, 2003, vol. 61, no. 1, pp. 163-185. DOI: 10.1016/S0022-1996(02)00056-9.
31. Stähler N., Thomas C. FiMod - A DSGE Model for Fiscal Policy Simulations. Economic Modelling, 2012, vol. 29, no. 2, pp. 239-261. DOI: 10.1016/j.econmod.2011.10.001.
32. Zubairy S. On Fiscal Multipliers: Estimates From a Medium Scale DSGE Model. International Economic Review, 2014, vol. 55, no. 1, pp. 169-195. DOI: 10.1111/iere.12045.
Review
For citations:
Lomonosov D.A. A DSGE Model of the Russian Residential Real Estate Market. Economic Policy. 2024;19(3):76-117. (In Russ.) https://doi.org/10.18288/1994-5124-2024-3-76-117
Views:
834
Email this article 