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The dynamic interactions between monetary policy and asset prices have conventionally been examined in terms of the asset price channel of transmission of monetary policy, given the pre-crisis analytical consensus against the use of monetary policy to respond directly to asset price inflation. In the post sub-prime crisis period, however, there has...
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... Granger causality analysis between house prices for the period 2003:Q2 to 2010:Q2, proxied by housing prices for the Mumbai city (dLHPI), stock prices (dLSENSEX_SA) and short-term interest rates measured by the weighted average call money rates (RCALL) provides some insights about the asset price dynamics (Table 3). Interest rate changes seem to Granger cause changes in house prices. ...
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In the last decade, advanced economies, including the euro area, experienced deflationary pressures caused by the global financial crisis of 2007-2009 and the anti-crisis policies that followed—in particular, the new financial regulations (which led to a deep decline in the money multiplier). However, there are numerous signs in both the real and f...
The literature on the monetary policy transmission mechanism identifies four distinct channels through which monetary policy can affect the real economy, namely: the direct interest rate effect; indirect effects via other asset prices; the exchange rate channel; and the
credit channel. The purpose of this paper is to utilize a structural vector aut...
In the last decade, advanced economies, including the euro area, experienced deflationary pressures caused by the global financial crisis of 2007-2009 and the anti-crisis policies that followed-in particular, the new financial regulations (which led to a deep decline in the money multiplier). However, there are numerous signs in both the real and f...
Citations
... For instance, Shibuya (1992) claims that as long as CPI and GDP deflator are stable, asset price inflation should not be taken as dangerous. On the other hand, Singh and Pattanaik (2012) suggest that consumer price index is not a healthy indicator of inflation trends as asset price inflation, and monetary authority should avoid credit bubbles and excess liquidity conditions, in order to prevent asset price bubbles. What both sides fail to take into account is the side effect on wealth distribution. ...
... Even though there is clarity about the objectives of monetary policy, yet ambiguity surrounds its use to influence asset price. Bordo and Wheelock (2004), Singh and Pattanaik (2012), and Taylor (2007) stress that monetary policy should not be used to control asset prices. Similarly, Christiano et al. (2008) and Leamer (2007) argue that asset bubbles arise from misread shocks, so they should not be targeted by monetary policy. ...
... Similarly, Mallick (2011) reiterates that the monetary policy helps in curbing the housing price despite the absence of sectoral targets like housing prices. Singh and Pattanaik (2012) find that housing credit growth is sensitive to the interest rate as impulse response reveals that tightening monetary policy results in moderation of credit demand over the medium-term. These developments, in turn, lead to lower real output. ...
This study attempts to examine the relationship between monetary policy and
housing prices in India. We use monthly data from January 2009 to December 2018
of four variables- Housing Price Index (HPI), Real Effective Exchange Rate (REER),
Gross Domestic Price (GDP), and interest rate for our estimations using the
Autoregressive Distributive Lag (ARDL) Model. The results from the study show that
the impact of monetary policy on housing prices is significant only on lag three;
however, the coefficient is very small. The results from the ARDL model are also
supported by the variance decomposition of housing price. The variance
decomposition of housing prices highlights that monetary policy explains around 13
percent of the variation in housing prices over a period of ten months. Further, the
accumulated impulse response function reveals that with one-unit shock to interest
rate results in a -0.000875 unit change in housing price. The study stipulates that,
since conventional monetary policy has a modest impact on housing prices, therefore, it is insignificant for addressing the problems of real estate in India.
... At the country level, for instance, Maysami, Howe, andRahmat (2005), Ewing (2002), Gupta and Reid (2013), Kyereboah-Coleman and Agyire-Tettey (2008), etc., have developed the relationship between stock market performance and different macroeconomic variables. However, in India, previous studies, such as Ghosh (2009), Bhattacharyya and Sensarma (2008), Pal and Mittal (2011), Singh and Pattanaik (2012), Sengupta (2014), and Prabhu, Bhattacharyya, and Ray (2015), have mainly focused on the impact of either monetary policy or macroeconomic factors on stock prices. It is probably the first study on India that scrutinizes the simultaneous effect of both monetary policy surprise and wide range of macroeconomic surprises on stock returns. ...
This study analyzes the sensitivity of a series of Indian stock indices for the astonishing component of monetary and macroeconomic policy with the data set from 1 April 2004 to 31 July 2016. The immediate impact is assessed with event analysis, and the dynamic effect is analyzed with the Vector Autoregression (VAR) model. The result of the event analysis indicates that the monetary policy surprise significantly affects the stock market and is more prominent than that of other macroeconomic surprises. Unlike the event study, the VAR analysis found that the other macroeconomic surprise also affects stock return. The study also highlights the industry effect and size effect, which is coherent with the predictions of the CAPM (Capital Asset Pricing Model) model. While many studies have been conducted on the monetary policy surprise in the developed economy, there are relatively few studies on macroeconomic surprises. Some studies conducted in India have analyzed the impact of monetary policy surprises on stock price; however, to the best of our knowledge, none of the studies has examined the simultaneous effect of both macroeconomic and monetary policy surprise. The study is relevant because the responses differ across sectors and vary with firm sizes. Thus, the study can effectively be used as a hedging instrument. Furthermore, the stock market acts as a vital channel for policy transmission and a critical decision driver for corporate finance. The understanding of firm and stock market dynamics against macroeconomic surprises can help policymakers in enhancing policy effectiveness and corporate finance professionals in improving decision-making.
... Moreover, according to another result, cash flow has not a remarkable effect on the change in housing prices by controlling the growth in the money supply. Singh & Pattanaik (2012) used structural VAR analysis to review the interactions between monetary policy and asset prices in India. While the asset price channel of monetary policy can prominently be seen in empirical results, there is no evidence about an intervention for developments in asset prices by the monetary policy. ...
The asset prices channel, as one of the transmission channels of monetary policy, refers to the process of changing aggregate demand level by affecting the asset prices of a change in the central bank's monetary policy decisions. There are 3 basic components of the asset price channels: stock price channel, housing price channel and exchange rate channel. In this study, the operation of the housing price channel is investigated by applying Panel VAR analysis. For this purpose, the data between 2009Q1-2017Q4 period for BRICT countries are analyzed and tested. The findings show that the housing price channel is operating in these countries.
The study consists of three parts. In the first part, the operation of the housing price channel is explained. In the second part, the literature research and in the third section, the empirical analysis are emphasized.
... Trends in Key Interest Rates 12 See RBI (2005), Mohan, R. (2008), Patra and Kapur (2010), Aleem (2010), Bhattacharya et al. (2011), Khundrakpam and Jain (2012), Kapur and Behera (2012), Mohanty (2012),Kletzer ((2012), RBI (2014),Das (2015). 13See Pandit, et al. (2006),Bhaumik et al. (2011),Bhatt and Kishor (2013) 14 SeeSingh and Pattanaik (2012), Khundrakpam. (2007),Bhattacharya et al. (2008),Khundrakpam and Jain (2012) ...
... Paucity of data in the Indian context rendered the use of house prices in testing the asset price channel infeasible. Moreover, Aleem (2010), Singh and Pattanaik (2012) and Singh (2012) find negligible real effects to monetary policy shocks via the equity price channel. As an explanation for this lack of importance of equity-based asset price channel of monetary policy, the RBI (2014) report state that "….during periods of high inflation, there is a tendency for households to shift away from financial savings to other forms of savings such as gold and real estate that tend to provide a better hedge against inflation." ...
As a commodity, gold occupies a special place in Indian psyche. With formal capital markets still out of reach for a large section of the Indian population, gold, beyond its traditional use as jewellery, also acts as a store of value, especially under an environment of moderately high inflation. In this paper, we further explore the asset price channel of monetary transmission by endogenizing gold price inflation within the Indian macroeconomic system. Supported by empirical tests in favor of such an inclusion, a linear VAR model results indicate that gold seems to act as a shock absorber by way of shielding other macroeconomic variables, especially GDP growth, from the influence monetary policy shocks. In India, the demand for gold is primarily met by imports. Thus, the dynamics of gold, real exchange rate and inflation are likely to be interlinked in a nonlinear manner. Based on estimation of a TVAR model and simulation methods of inference, we find that there are significant differences in the macroeconomic dynamics of the Indian economy under high and low inflation regimes. Moreover, the TVAR model results suggest that gold seems to matter more in the Indian macroeconomic system during episodes of high inflation.
Understanding trends in regional house prices and whether they converge to a single steady state or form clusters are important issues. These trends have been studied at length in respect to advanced and emerging market economies (EMEs). However, the trends are not understood well in the context of a major and populous EME such as India, which can offer vital policy insights for other countries. Using residential house price data for fifty cities, this study showed that house prices do not converge to a single steady state in India. Rather these prices form three clusters wherein they converged to their respective steady-state paths and displayed conditional convergence. Higher initial house price, home loan, rent, population density and literacy were associated with an increased probability of higher house price club. City inflation, on the contrary, increased the chances of association with lower-price clubs. Similar dynamics of housing clusters can enable policymakers to probe the common driving factors and accordingly devise cluster-specific policy measures. There is no study, so far, on club convergence of house prices for India; so this study contributes to this gap in the literature.
This paper sets the objective of estimating the mediating role of asset prices in the transmission of monetary policy. Vector autoregressive model comprising short-term interest rate, output, inflation and asset prices has been estimated using data of Pakistan economy for the period 2000m01 to 2019m06. We find significant role of asset prices in transmission of monetary policy to target variables, especially when individual asset prices are taken instead of asset price index. Stock prices are found important mediator of transmission from interest rate to output while exchange rate is so for inflation rate; role of house prices remains moderate.
This article investigates monetary policy and stock market interaction across 41 developed and developing economies using GMM-Panel VAR model. The analysis is undertaken in two sub-periods—before and after the crisis of 2008 to make a comparative assessment of whether the relationship between monetary policy and stock prices altered in the aftermath of the crisis. We verify the existence of different channels of monetary transmission to stock prices. Our results point to the prevalence of discount rate channel of monetary policy in affecting stock prices after the crisis of 2008. Further, our results indicate an important role of excess liquidity in pushing stock prices upward in developed economies in the post-crisis period. In developing economies, term premia channel is the dominant channel of transmission to stock prices. Also, we find evidence of monetary authorities of developed economies responding directly to stock price movements to ensure financial stability in the post-crisis period. Central banks react primarily to inflationary pressures by tightening monetary policy both before and after the crisis in developed and developing economies.
JEL Codes: C32, E44, E52, F42
This study is aimed at examining the dynamic relationship between real housing prices (RHP) return and economic policy uncertainty (EPU) using a panel vector autoregressive (PVAR) approach and annual data for a panel of panel of 16 countries over the period 2004–2018. The study includes economic growth, short-term interest rate, and population as additional covariates. Empirical results show that a positive shock to EPU leads to a decrease in housing prices with EPU showing only a weak response to housing price shocks. This implies that EPU has a robust predictive power for the housing market, implying the need for evaluating the associated risks. The panel Granger causality tests indicate strong and robust Granger causality from the EPU to housing prices, but not vice versa. The causal links also indicate that the effect of the EPU on RHP is direct rather than indirect through other variables. Based on these outcomes, policy recommendations are made for real estate agents, portfolio managers, and policy makers.
