Purpose This study aims to investigate the behavioural biases influencing the real estate market investing decisions of normal non-professional investors in India. Design/methodology/approach As the study involves the behavioural data with polytomous response format, psychometric test- graded response model (IRT approach) was used for the study with the help of STATA 14. Multi-stage stratified sampling was used to collect a sample of 560 respondents. The study used a 14-item scale representing behavioural biases derived from two broad behavioural theories, i.e. heuristics and prospect theories. Sample characteristics were checked using SPSS 20. Pre-required assumptions for IRT (i.e. local independence and unidimensionality) were tested by CFA using AMOS 20. Findings Five items, four of which belong to heuristics (anchoring – 2, representativeness – 1 and availability bias – 1) and one belong to prospect theory (regret aversion) are sufficient to measure the behavioural attitude of real estate investors in the Indian scenario. Item discrimination ai ranged from 0.95 to 1.52 (average value 1.29), showing moderate discrimination power of the items. The items have done a pretty good job of assessing the lower level of agreement. For the higher level of agreement, the scale came out to be less precise, with less information and higher standard error of measurement. Research limitations/implications As the behavioural biases are often false, the study suggests the investors not to repeat these nasty biases to improve investment strategies. As they are shared and not easily changeable, understanding these biases may also help them in beating the market by acting as “noise traders”. Practical implications The traditional price index is incomplete in some essential respects. The inclusion of these behavioural biases into the construction of price index will greatly improve the traditional price index, policymakers should seriously think about it. Social implications Shelter is one of the basic needs; a dwelling unit is needed for one to stay in, develop and contribute to economy and society. If investors try to minimise these biases and policymakers keep a track of these while making strategies, mispricing in this sector can be controlled to some extent, which will ultimately help in the well-being of society. Originality/value This study contributes to the limited research by investigating the behavioural biases influencing the real estate market investment decisions of normal non-professional investors. It contributes to the lacking academe on real estate market in India. The study has used a psychometric test, i.e. the item response theory, for evaluating the quality of the items.

Purpose The purpose of this study is to explain the relationship between behavioural biases, investment satisfaction and reinvestment intention considering the effect of evolutionary psychology. The study believes that biases are not at all times bad; sometimes, biases can assist the individual investor to select the top course of action and allow them to go for the less costly mistakes, thereby helping in achieving satisficing behaviour. Design/methodology/approach Data were collected using structured and a close-ended questionnaire from a sample of 560 respondents by using multi-stage stratified sampling method. PLS-SEM was used for preliminary validation of the questionnaire. Mediation model using the structural equation model (SEM) with the help of AMOS 20 was used for the analyses. Pre-requisite assumptions for SEM were checked by using sample characteristics. The study has three constructs with multiple items; hence, the instrument validation was done by measuring the construct validity and reliability using Cronbach’s alpha, exploratory factor analysis and confirmatory factor analysis with the help of SPSS 20 and AMOS 20. Findings The study confirms that behavioural biases influence investment decisions in the real estate market. Further, investment satisfaction is found to have a significant and complementary partial mediating effect. The positive mediating effect of investment satisfaction between behavioural biases and reinvestment intention shows that biases are natural tendencies in response to limit to learning which can be explained by evolutionary psychology. Research limitations/implications There are chances that the result obtained here is because of myopic decision-making behaviour in which the long-time horizon is not considered and behavioural biases, as well as evolutionary psychology, are adaptive, so the result may change in the long-time horizon, which seeks further investigations. The study talked about the relationship between behavioural biases, investment satisfaction and reinvestment intention; it will be interesting to bring some more constructs in this model, for example, investment intention and reinvestment behaviour; this can deliver a more precise picture in this regard. Practical implications Understanding such relationships will help in better clarity about the way investment is made. The study confirms that market behaviour in the real estate market is sub-optimal, which shows that there is an opportunity for attentive investors by trading and gathering on information. Real estate practitioners can get clues from market anomalies and investor phenomena; understanding these may suggest ways to use them in the market. Social implications Reforms in the housing sector do not only satisfy one of the basic needs but also leads to holistic economic development. Besides direct contribution, it contributes to social capital. Originality/value The study extends the current knowledge base about the relationship between behavioural biases, investment satisfaction and reinvestment intention. This study investigates the behavioural biases influencing the real estate market investment decisions of non-professional investors considering the effect of evolutionary psychology.

Purpose The purpose of this paper is to study the effect of the 2008 global financial crisis on housing market dynamics in an emerging economy like India using quarterly data (Q4 2008–2009 to Q1 2018–2019). The study explores the extent of linkages between housing prices, monetary policy and financial stability by explaining the nature of the shocks to the housing sector and the degree of impact of those shocks; the possibility of adverse feedback loop which is beyond the natural levels; and the usefulness of explicit and direct role of monetary policy for the housing market stability, which was the loudest demand immediately after the crisis. Design/methodology/approach The paper follows a three-step methodology: data transformations, a variable selection process “general-to-specific modelling” with the help of OxMetrics 6 Package, and vector autoregressive modelling with the help of EViews 10. F-test was used to describe the short-term relationships between the variables. Impulse response and variance decomposition were used to explain the type of relationship (negative or positive) and the period of the relationships, respectively. Findings The study finds that the housing sector is sensitive to the monetary policy shocks, whereas the contribution of the housing market shocks to the fluctuations in other market variables is not substantial, though not negligible. As far as the nature of the shocks is concerned, the observed dynamics in the real house prices are diverging from their fundamental levels. The housing market shocks are more or less static; it rules out the chances for a self-reinforcing feedback loop with the existing setup. Research limitations/implications The study concludes that the observed dynamics in the real house prices are diverging from their fundamental levels. Given the limitation, the researchers could extend this study by decomposing the part of the risk to the sector contributed by the other drivers, which may be inherent imperfections in housing markets, weak and unreliable wealth effect, and the presence of behavioural biases. Practical implications The present study finds countercyclical measures to be more useful for this sector as compared to the forward-looking monetary policy reforms in this sector. The central bank in India should continue to refrain from responding directly to the housing sector fluctuations. Investors can enjoy investing in the housing sector without any fear of the crisis as of now. The effect of speculation is small but not negligible, which enjoins the investors and the policy-makers to remain watchful. Interest rate, money supply and inflation lead (Granger-cause) the housing prices. This information is relevant for spending and investment decisions. Social implications The study feels that banks should avoid using monetary policy to balance the house prices. This will be beneficial both for the economy and the society, as any change in monetary policy to especially curb out surging housing prices may adversely affect the output, and finally, may lead to the deflation. The fear of deflation may cause devastating economic, financial and social effects. Originality/value The study contributes to the literature by shedding some new insights about the interrelationship between macroeconomic variables, housing prices and financial stability in the aftermath of the 2008–2009 financial crisis. Such types of studies are absent from emerging markets, particularly from India.

PurposeThe purpose of this study to evaluate the evolving market efficiency of the housing market under the framework of adaptive market hypothesis and martingale difference hypothesis taking a case of India.Design/methodology/approachThe study used a wild bootstrap version of the generalized spectral (GS) test in the rolling window framework to measure possible time-varying linear and non-linear dependence in the housing market.FindingsThe study finds that the Indian housing market, in general, is not efficient, and this efficiency is dynamic, which changes with time lending support to the adaptive market hypothesis. The study confirms that the evolutionary model of individuals adapting to a changing environment via behavioural biases affects the efficiency of the housing market, which leads to the evolving efficiency of the housing market prices.Research limitations/implicationsThe study believes that the potential implications go beyond evolutionary forces and the adaptive market hypothesis , which, does not only depend on an individual's decision-making process but also on social psychology. Thus, a further attempt in this line, taking into account the social psychology and quantitative rigour towards drivers of evolving efficiency is suggested for future research.Practical implicationsThe study suggests that there is a possibility of extra returns for market players, but not always. The Indian housing market has witnessed several landmark reforms in recent years, so it is believed that these reforms would decrease the inefficiency level of this market. Contrary to this, the study’s findings reveal an increase in the inefficiency level in recent years. As the Indian housing market shows evolving efficiency, it is believed that the increased inefficiency is temporary. The increased inefficiency can be regarded as the settlement stage of the various policy and technical reforms.Originality/valueConfirming the presence or absence of adaptive efficiency in the housing market under possible non-linear dependence will be a significant addition to the existing literature.