| Summary: | 碩士 === 中原大學 === 國際經營與貿易研究所 === 106 === The study builds a panel smooth transition vector autoregression model (PST-VAR model) and uses the constructed financial technology index (FinTech index) as the transition variable to assess the time- and country-varying threshold causality between stock returns, housing returns, and economic growth. In empirical, we adopt 24 member countries of the Organization for Economic Cooperation and Development (OECD) during 2000-2016 (a total of 408 observations) as sample objects. The FinTech index is calculated by adding up the 12 standardized component indicators suggested by Hieminga and Lande (2016).
Empirical results are summarized as follows:
First, there exist unilateral or bilateral time- and country-varying threshold causalities between stock markets, housing markets, and economic growth, depending on the threshold of the FinTech index. However, the causalities are constant in the traditional linear VAR model.
Second, there is a unilateral threshold causality running from economic growth to stock market, and the impact becomes obvious as the FinTech index is over the threshold 86.03. However, the causality is bilateral in the traditional linear VAR model.
Third, there is a constant, positive two-way causality between the housing markets and economic growth in the traditional VAR model, and a time- and country-varying two-way causality in the PST-VAR model. Moreover, the causality weakens as the FinTech index is over the thresholds.
Fourth, there exists a negative, unilateral causality from stock prices to housing prices in the traditional VAR model and a unilateral threshold causality in the PST-VAR model. Increase in the one-period lagged stock prices would pull down current housing prices as the FinTech index is below the threshold 68.15 and push up current housing prices as the FinTech index is over the threshold.
Fifth, the bonus of economic growth would significantly stimulate stock prices one-period latter and housing prices two-period latter. The stimulation still works in the stock markets and would reverse in the housing markets as the FinTech index is above the threshold value.
The associated policy suggestions are listed as follows:
First, there is a time- and country-varying causality between stock markets, housing markets, and economic growth. Thus, the investors, firms, and governments in individual countries should evaluate the causality period by period to avoid making wrong strategies and decisions,
Second, investors should choose the stock markets of the countries with economic growth and high FinTech development as the investment targets. Once the stock prices begin to rise, they can then invest in the countries’ housing markets. When the housing prices star to rise, they will feed back into economic growth.
Third, if the development of FinTech is inevitable, the OECD countries should adopt proper policies to promote the economic growth. Because the growth would drive the upward development of the stock and housing markets, which further generates feedback effects in the growth.
Fourth, investors in the countries with low FinTech index (e.g., below the threshold 68.15), the economic growth cannot significantly boost the stock markets, and the rise of stock prices would depress the housing prices. Thus, they would sell housing once the stock prices rise.
|
|---|
