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Purpose

This paper aims to identify the economic stimulus measures that ensure stability of the Lithuanian housing market in the event of an economic shock.

Design/methodology/approach

The econometric analysis includes stationarity test, Granger causality test, correlation analysis, autoregressive distributed lag models and cointegration analysis using ARDL bounds testing.

Findings

The econometric modelling reveals that the housing price in Lithuania correlates with quarterly changes in the gross domestic product and approves that the cycles of the real estate market are related to the economic cycles. Economic stimulus measures should mainly focus on stabilizing the economics, preserving the cash and deposits of households, as well as consumer spending in the case of economic shock.

Originality Value

This study is beneficial for policy makers to make decisions to maintain stability in the housing market in the event of any economic shock.

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