Cognitive Dissonance Under Policy Shock: The Psychological

Transmission Mechanism of China's "Houses Are for Living in, Not

for Speculation" Policy on Investor Behavior

Haofei Guo

Beijing City University, School of International Culture and Communication, Haidian,101309, China

Keywords: Houses Are for Living in, Not for Speculation, Cognitive Dissonance, Investor Behavior, Policy Optimization,

Real Estate Market.

Abstract: With the deepening implementation of China’s "housing for living, not for speculation" policy, investors in

the real estate market are increasingly experiencing cognitive dissonance. Against the backdrop of soaring

housing prices and resource misallocation in China’s real estate market, this article systematically analyzes

the causes and manifestations of such dissonance under this policy framework and proposes optimization

strategies. The study identifies policy ambiguity, information distortion, and investor psychological biases—

including the disposition effect, loss aversion, and anchoring bias—as primary drivers of cognitive dissonance.

To address these issues, solutions are proposed from dual perspectives: refining policy instruments and

optimizing investor behavior. Specific recommendations include enhancing policy transparency, improving

information disclosure mechanisms, strengthening policy expectation management, and encouraging

investors to deepen financial knowledge learning. These measures aim to help investors better adapt to the

policy environment, reduce cognitive dissonance, and promote the stable and healthy development of the real

estate market.

1 INTRODUCTION

1.1 Background to the Selection of

Topics

The rapid development of China's real estate market

has caused a series of problems, and the irrational

surge in housing prices in some cities is particularly

serious. According to data from the National Bureau

of Statistics and the China Index Research Institute

(CREIS), the growth of house prices in core cities and

the growth of residents 'income from 2015 to 2023

significantly deviated, showing obvious irrational

characteristics. This surge not only exceeds the

purchasing power of ordinary citizens but also creates

a double bubble that includes price and quantity at the

structural level. For example, in the first-tier city of

Shenzhen, the average price of new commercial

housing in 2023 will reach RMB 65,000 per square

meter, up 97% from RMB 33,000 per square meter in

2015. In core areas like Nanshan, the price per square

meter exceeds 100,000 yuan, and the price-to-income

ratio reaches 35.5:1 (National Bureau of Statistics,

2023). Similarly, in the second-tier city of Chengdu,

the average price of new housing in its High-tech

Zone in 2023 will rise to 32000 yuan per square meter,

an increase of 167% compared with 12000 yuan per

square meter in 2015, bringing the price-to-income

ratio to 18:1 (Figure 1). A China Real Estate

Association (CRIC) study of 100 key cities further

indicates that in 2023, core cities like Shenzhen and

Sanya maintained price-to-income ratios as high as

35.5 and 30.8, respectively, while third- and fourth-

tier cities generally registered ratios below 10 (e.g.,

4.3 in Zhuzhou), revealing significant regional

divergence (Zhuge Research Institude, 2024) (Figure

2). Price bubbles occur when housing values

substantially exceed intrinsic worth, whereas quantity

bubbles arise when supply drastically outpaces

demand. This dual-bubble phenomenon poses latent

risks to socioeconomic stability and has consequently

drawn heightened government attention.

Guo, H.

Cognitive Dissonance Under Policy Shock: The Psychological Transmission Mechanism of China’s "Houses Are for Living in, Not for Speculation" Policy on Investor Behavior.

DOI: 10.5220/0014361000004718

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence (EMITI 2025), pages 447-456

ISBN: 978-989-758-792-4

447

Data source: National Bureau of Statistics of China. China Statistical Yearbook (2023)

Figure 1: Trend of Housing Price to Income Ratio in Core Cities (2015-2023)

Data source: Zhuge Research Institute. (January 23, 2024). "Research Report on the Housing Price-to-Income Ratio of 100

Key Cities". Zhuge Research Institute Official Website. Retrieved from https://example.com/report-link

Figure 2: Comparison of the average housing price-to-income ratio of 100 key cities in China and that of first-tier cities (2020-

2023).

In addition to housing bubbles, excessive

speculative behavior has led to misallocation of land

and credit resources, as well as severe imbalances in

housing supply and demand. This imbalance has not

only intensified social tensions but also impeded

healthy economic development. To address this, the

Chinese government introduced the "housing is for

living in, not for speculation" policy, which aims to

curb rapid housing price growth through targeted

measures and promote stable, healthy development of

the real estate market.

The policy's implementation has significantly

impacted investors. By restricting speculative home

purchases, it has triggered cognitive dissonance

among some investors. Cognitive dissonance theory

posits that individuals experience psychological

discomfort when perceiving inconsistencies between

their attitudes or between attitudes and behaviors;

they subsequently attempt to reduce this discomfort

by adjusting either attitudes or behaviors (Liu et al.,

2020). In the real estate investment environment, this

inconsistency reflects investors 'confusion about

future market trends. On the one hand, they realize

that unreasonable price surges are unsustainable. On

the other hand, they are difficult to give up their

dependence on real estate investment and related

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20000

30000

40000

50000

60000

70000

80000

2015 2016 2017 2018 2019 2020 2021 2022 2023

Housing Price, Shenzhen Housing Price, Chengdu

Housing Price to Income Ratio, Shenzhen Housing Price to Income Ratio, Chengdu

14.2

13.5

12.3

11.5

32.5

29.5

28.5

2020 2021 2022 2023

100 Key cities First-tier cities

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448

return expectations. This psychological state has an

adverse impact on investment decisions and may also

aggravate market volatility.

1.2 Objectives and Significance of the

Research

This paper provides an in-depth analysis of the

psychological mechanisms and behavioural

manifestations of different types of investors

'cognitive dissonance under China's "housing is for

living in, not for speculation" policy, revealing how

this dissonance hinders the effective transmission of

policies. This research aims to formulate targeted

optimization strategies through a two-pronged

approach, improve policy tools based on behavioural

economics principles, and guide investors to make

behavioural adjustments. These coordinated efforts

aim to resolve cognitive conflicts, improve the

effectiveness of policy implementation, and

ultimately promote stability in the real estate market.

2 BASIC FACTS ABOUT

POLICIES AND INVESTOR

2.1 Policy Framework and Tool Map

2.1.1 Policy Tool Map

The "housing is for living, not for speculation" policy

contains extensive and in-depth measures, mainly

targeting multiple dimensions including housing

demand, supply and differentiated credit policies.

Overall, these interventions constitute a

comprehensive policy toolkit designed to curb

excessive housing price increases from multiple

perspectives and guide the real estate market towards

rational development.

At the 2016 Central Economic Work Conference,

the principle that "a house is for living in, not for

speculation" was officially established. The

conference called for integrated deployment of

financial, land, fiscal, investment, and legislative

instruments to accelerate the development of

fundamental systems and long-term mechanisms

compatible with national conditions and market

principles. Subsequently, numerous cities

implemented purchase and loan restrictions.

Demand-side interventions since 2016 have

centered on purchase restrictions, loan controls, and

sales regulations. Following the central government's

2016 pilot restrictions in major cities, policies such as

Shenzhen's "Eight Measures" and Shanghai's "Nine

Measures" were successively introduced. The 19th

National Congress report (October 2017) reaffirmed

the policy while proposing a dual rental-purchase

housing system. In July 2018, the Central Politburo

emphasized the imperative to "resolutely curb

housing price increases" and established the "Three

Stabilities" objectives: stabilizing land prices,

housing prices, and market expectations. The "Real

Estate Loan Concentration Management System"

(December 2020) imposed bank-level caps on real

estate loan proportions to mitigate financial risks.

Supply-side measures include land supply

optimization, housing structure reform, and financing

regulation. The July 2023 Central Politburo meeting

advocated "adapting to new real estate supply-

demand dynamics" and optimizing instruments like

the "Two-Concentration" land supply system

(centralized announcements and transfers). The

"Three Red Lines" policy imposes critical financial

constraints on developers to transition from high-

leverage expansion to sustainable operations,

representing a core initiative for real estate "de-

financialization." These thresholds comprise:

 Asset-liability ratio (excluding presales) ≤

70%: Measures actual corporate debt levels

 Net gearing ratio ≤ 100%: Limits net debt to

equity

 Cash-to-short-term debt ratio ≥ 1: Requires

sufficient liquidity to cover maturing obligations

Policy instruments have evolved from singular

measures (e.g., 2010 "Ten National Measures") to

multidimensional frameworks incorporating

purchase restrictions, price caps, and financial

transparency—exemplified by 2021's second-hand

housing guidance prices.

2.1.2 Manifestations and Causes of Local

Implementation Disparities—A

Perspective from the "Promotion

Tournament" Theory

Zhou Li’an (2007) proposed the "promotion

tournament" model, highlighting the powerful

incentive mechanism that drives Chinese local

officials to prioritize economic growth (Zhou, 2007).

This framework elucidates the variability in local

implementation of the "housing for living, not for

speculation" policy.

First-tier cities (e.g., Beijing, Shanghai,

Guangzhou, Shenzhen) typically enforce the strictest

regulatory standards. Shanghai includes judicial-

auctioned properties in purchase restrictions, while

Shenzhen implements a second-hand housing

Cognitive Dissonance Under Policy Shock: The Psychological Transmission Mechanism of China’s "Houses Are for Living in, Not for

Speculation" Policy on Investor Behavior

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reference pricing system. These cities exhibit strong

economic foundations and low land finance

dependence—Shenzhen’s land-related revenue

constitutes <20% of fiscal income. Consequently,

officials impose rigorous controls to gain central

government recognition and bolster political capital

for promotion.

Second-tier cities (e.g., Hangzhou, Chengdu)

demonstrate dynamic policy adjustments aligned

with market conditions. In 2023, Hangzhou relaxed

suburban purchase restrictions to stimulate peripheral

inventory clearance. Facing dual pressures of

sustaining GDP growth and stabilizing housing prices,

local officials balance participation in the promotion-

driven "GDP competition" with compliance to central

directives.

Third- and fourth-tier cities, where land finance

dependence often exceeds 50%, employ indirect

regulatory relaxation through "talent subsidies" and

"group purchase discounts" to maintain fiscal revenue.

Examples include Heze’s removal of resale

restrictions and Zhumadian’s reduction of down

payment requirements—measures strategically

designed to bypass central regulatory constraints.

2.2 Behavioral Traits and Structural

Stratification of Investors

The investor structure of China's real estate market

exhibits clear stratification, with distinct differences

among various groups in investment motivations,

asset allocation, and risk preferences. Based on data

from the China Household Finance Survey (CHFS)

and market research, investors can be categorized into

the following three types.

Institutional investors, represented by insurance

capital and REITs funds, exhibit long-term and stable

investment behavior. They favor asset types with

steady cash flows, such as commercial real estate and

logistics parks, aiming to generate rental income and

achieve capital appreciation by holding high-quality

properties. For example, in 2024, industrial parks and

warehousing logistics projects accounted for 58% of

the underlying assets in domestic public REITs (Guo

et al., 2024).

High-net-worth households are the primary

drivers of real estate investment; however, their asset

allocation tends to be highly concentrated, with

significant dependence on property. According to the

latest data, in 2023, housing assets made up

approximately 61% of the total assets of Chinese

households (Ren, 2024). This indicates that real estate

continues to play a significant role in the asset

allocation of Chinese households. Real estate assets

make up 41% of individual investments in China

(Marjerison et al., 2021). It was one of the most

popular investment methods at the time, with wealth

appreciation achieved through "using property to

service loans" or cross-regional allocation, such as in

the Yangtze River Delta and Pearl River Delta city

clusters.

According to the 2024 Hurun Report, the

proportion of high-net-worth families investing in

real estate has dropped to 5%, with a growing

preference for corporate equity and financial assets.

However, many still retain high-quality properties in

core cities as a hedge against inflation, indicating a

trend toward risk management and strategic

transformation.

Small and medium investors tend to have

undiversified asset allocations. According to the

"China Household Wealth Survey Report 2019,"

93.03% of resident households owned one residential

property in 2018 (China Household Welath Survey

and Research Center, 2019). However, the "China

Urban Household Wealth Health Report" (2023)

(China Household Finance Survey and Research

Center, 2023) shows that cash and deposits account

for 88% of Chinese households' financial assets. In

addition, the net value of real estate accounts for

71.35% of per capita household wealth in urban areas

and 52.28% in rural areas. The narrow range of

investment options has resulted in excessive reliance

on real estate for wealth preservation.

Moreover, small and medium investors are easily

influenced by social media in their decision-making.

A survey conducted by DT Business Observer (2025)

found that over 80% of households had cut back on

non-essential spending such as education and travel

due to mortgage pressure, while 52.9% had postponed

other major purchases. Given their high sensitivity to

debt, most households are considered risk-averse,

lacking independent judgment and being easily

misled by one-sided information on short video

platforms—such as "real estate speculation tips" or

"huge profits from school district housing"—which

often leads to irrational herd behavior in home buying.

Small and medium investors also face liquidity

risks. Survey data indicate that low-income

households are significantly more vulnerable to

income losses than higher-income borrowers, with

approximately 20% of households in the lowest

income quintile having experienced substantial

income loss, compared to only 4% of households in

the top income quintile (Wang, 2022). Because real

estate assets are difficult to liquidate, low-income

households face greater pressure to repay debt during

economic downturns.

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3 POLICY LOGIC AND THE

MECHANISM BEHIND THE

EMERGENCE OF COGNITIVE

DISSONANCE

3.1 Core Motivations for Implementing

the Principle of “Houses Are for

Living in, Not for Speculation”

3.1.1 Economic De-Real Estate

Transformation

The core motivation behind the government's

implementation of the "housing is for living, not for

speculation" policy lies in addressing the long-

standing issues of excessive speculation and housing

price bubbles in China's real estate market.

This policy was introduced to guide the real estate

market to return to its basic function of providing

housing rather than just as an investment tool. It is

also implemented out of the need to reduce financial

risks. Its implementation is also driven by the need to

mitigate financial risks. Excessive speculative

behavior not only inflates housing prices but also

increases market volatility. For example, speculators

often use leverage—such as business and consumer

loans—to hoard properties in the short term, creating

a false sense of supply-demand imbalance, pushing

up prices, and generating an illusion of market

prosperity. This illusion encourages real estate

companies to aggressively acquire land using high

levels of debt. Combined with surging land costs, this

behavior directly contributes to the rapid expansion

of corporate debt.

Data show that when the debt-to-GDP ratio of real

estate companies becomes excessively high, it

indicates that their debt levels have far exceeded the

economy’s capacity to sustain them. If sales revenue

slows—due to policy tightening or a market

downturn—high interest payments and maturing debt

obligations can trigger a chain of defaults. A large

body of empirical research, including studies by

Borio & Drehmann (2009), Drehmann & Juselius

(2013), and Gertler & Hofmann (2016), has shown

that credit expansion plays a key role in the formation

of asset bubbles and financial crises. Domestic credit

has been identified as a critical leading indicator of

financial instability (Ji et al., 2017).

3.1.2 Demands for Social Equity

The price-to-income ratio, defined as the median

housing price divided by the median annual

household income, serves as a key indicator of

housing affordability. In 2023, this ratio reached as

high as 25:1 in first-tier cities, with Shenzhen hitting

35.5:1. This means that an average household would

need to save every penny for 25 years to afford a

home, far surpassing the international warning

threshold of 9:1. Research has shown that once the

house price-to-income ratio surpasses 9:1, the net

contribution of the real estate sector to economic

growth turns from positive to negative (Caijing

Strategy Research Institude, 2019).

At the same time, this extreme imbalance has

directly led to two major social issues: housing

anxiety among young people and a worsening of

intergenerational wealth disparity. According to the

"China Household Wealth Index Research Report

2021Q1," in the first quarter, over 70% of household

wealth growth was attributed to housing assets.

Households that owned property saw an average

annual wealth increase of 12.3%, while young people

without property experienced a growth of only 3.8%

(Caixin, 2021). This differentiation results in dual

economic consequences. First, a decline in the youth

entrepreneurship rate has been observed. According

to the China Youth Entrepreneurship and

Employment Foundation (2023), the "China Youth

Entrepreneurship Development Report 2023"

indicates that China's youth entrepreneurship

intention index dropped by 22% in 2023 compared to

2015, highlighting the significant dampening effect of

high housing prices on young people's motivation to

start businesses (China Youth Entrepreneurship and

Employment Foundation, 2023). Second, there has

been insufficient investment in educational capital

among the younger generation. A 2019 study by the

School of Economics and Business Administration at

Beijing Normal University found that rising urban

housing prices exert a significant crowding-out effect

on household education spending. Based on data from

35 large and medium-sized cities between 2002 and

2017, the study revealed that a 1% increase in housing

prices leads to a 0.4 percentage point decrease in the

share of educational expenditure by rural households.

The imbalance in educational spending is even more

pronounced in cities with high housing prices (Yan,

2020), thereby undermining the long-term potential

for economic growth.

Therefore, the "housing is for living, not for

speculation" policy was introduced to ease the

rigidity of housing costs, promote upward mobility

among young people, and pave the way for long-term

equitable mechanisms such as equal rights for renters

and buyers.

Cognitive Dissonance Under Policy Shock: The Psychological Transmission Mechanism of China’s "Houses Are for Living in, Not for

Speculation" Policy on Investor Behavior

451

3.2 Causes and Manifestations of

Investor Cognitive Dissonance

3.2.1 Mechanisms Driven by Psychological

Effects

Odean, T noted that individual investors tend to sell

winning assets and hold on to losing ones (Odean,

1998). In other words, investors often retain

underperforming assets to avoid the psychological

discomfort of realizing losses, while selling profitable

assets too early to secure gains.

Consistent with the view that this investment

behavior is a mistake stemming from limited

cognitive ability or low financial literacy, the

disposition effect is most pronounced among

financially unsophisticated investors. For instance,

the disposition effect is generally stronger among

individual investors than among institutional

investors (Brown et al., 2006; Chen et al., 2007; Choe

& Eom, 2009; Barber et al., 2007).

Calvet, L. E., Campbell, J., & Sodini, P. (2009)

noted that less sophisticated households are more

likely to sell winners and hold losers. As a result, this

disposition effect is particularly evident among

general individual investors in the real estate sector.

In their analysis of prospect theory, Kahneman

and Tversky (1979) stated: "A salient characteristic of

attitudes to changes in welfare is that losses loom

larger than gains. The aggravation that one

experiences in losing a sum of money appears to be

greater than the pleasure associated with gaining the

same amount". Loss aversion is one of the core

features of prospect theory. In the real estate market,

investors tend to fear falling housing prices more than

they desire rising prices. This asymmetry leads them

to make irrational decisions—either overly

conservative or excessively risky—when prices

decline, in an effort to avoid losses. The analysis also

incorporates the value function: "The value function

is normally concave for gains, commonly convex for

losses, and is generally steeper for losses than for

gains" (Tversky & Kahneman, 1979). The asymmetry

of the value function suggests that the pain of losses

exceeds the pleasure of equivalent gains. This

imbalance makes investors more sensitive to price

declines and more likely to behave irrationally to

avoid losses, thereby amplifying their fear of falling

housing prices. Such asymmetric reactions often

result in investors refusing to sell at lower prices,

even when facing liquidity crises. The endowment

effect is a specific manifestation of loss aversion,

referring to the tendency of individuals to assign

higher value to items they own, even when these

items are objectively indistinguishable from similar

items they do not possess. This effect reflects an

irrational preference for goods already owned,

causing individuals to charge higher prices when

selling them and lower prices when purchasing them.

As a result, the irrational behavior of investors in the

real estate market has further intensified. Due to the

endowment effect, investors incur psychological

costs when considering selling their properties, which

makes them reluctant to accept prices lower than their

own valuation even if market conditions change.

In the real estate market, this psychological

phenomenon can have several major consequences. It

could lead to a shortage of housing supply because

many property owners are reluctant to sell at prices

they believe are "losing money." The endowment

effect could exacerbate market volatility because

investors are more likely to hold properties than sell

when prices fall, which could prolong the market

adjustment period. Finally, this phenomenon may

reduce market liquidity, as differences in price

expectations between buyers and sellers can cause

transactions to be delayed or failed.

In many cases, people will start with an initial

value and then adjust the initial value to arrive at the

final answer. The initial value, or starting point, may

be implied by the expression of the problem or may

be the result of part of the calculation process. In

either case, the adjustments made are often

insufficient. In other words, different starting points

will lead to different estimates, and these estimates

will be biased towards the initial values. People call

this phenomenon the anchoring effect (Tversky &

Kahneman, 1974). In the field of behavioural

economics, anchoring effects, as the core mechanism

of decision-making bias, have been proven to

profoundly affect investors 'perceptions and

behaviors in the real estate market. Since the

pioneering introduction of anchoring theory by

Tversky and Kahneman in 1974, subsequent research

has revealed how it works in complex economic

environments. The real estate market, characterized

by high value, information asymmetry and long-term

investment cycles, has become a typical scenario

where anchoring effects can be significantly observed.

The real estate market, characterized by high

value, information asymmetry and long-term

investment cycles, has become a typical scenario

where anchoring effects can be significantly observed.

When historical highs are used as a benchmark,

current market prices may still be considered

"undervalued" even if underlying fundamentals have

changed and prices have fallen. This over-reliance on

initial information can cause investors to ignore key

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market signals and ultimately lead to irrational

investment decisions.

From a cognitive psychology perspective,

investors naturally rely on "anchored adjustment"

heuristics when evaluating the value of a property.

Historical prices, developers 'pricing strategies and

listing prices of surrounding properties can all serve

as initial reference. An experimental study conducted

by the University of Tilburg in the Netherlands in

2019 found that when participants were shown

different initial price information for a property, even

if they were clearly told that the prices had no actual

reference value, their subsequent valuations still

showed significant anchoring bias, which was usually

adjusted by less than 40% (University of Tilburg,

2019). This cognitive inertia stems from the brain's

tendency to simplify information processing by

transforming complex tasks of value assessment into

limited adjustments based on anchors, resulting in

systematic deviations from rational expectations.

In real estate investment behavior, analysis by the

U.S. real estate data platform Zillow indicates that, on

the eve of the 2008 subprime mortgage crisis, over 65%

of investors continued to use pre-crisis historical peak

prices as valuation anchors, ignoring critical signals

such as tightened credit policies and rising default

rates (Zillow Research, 2020). This bias resulted in

persistently overvalued asset prices, ultimately

leading to a market collapse. Therefore, in his

research on global real estate bubbles, Professor

Shiller of Yale University pointed out that even when

clear warning signs emerge in the market, investors

tend to cling to their initial perceptions due to

anchoring bias, leading to collective irrational

behavior (Shiller, 2015).

3.2.2 Interaction Between Policy

Environment and Behavior

The ambiguity of the policy environment is primarily

reflected in the frequent fluctuations of local

implementation standards and the vague language

used in policy documents. Significant regulatory

discrepancies are observed at the local level: first-tier

cities generally adopt the strictest regulatory

measures, while third- and fourth-tier cities tend to

ease restrictions under the guise of "talent subsidies"

and similar programs. This inconsistency in

enforcement, combined with the unclear distinction in

policy texts between "supporting reasonable demand"

and "curbing speculative investment," has led to

persistent instability in market expectations.

The vagueness in policy language further

exacerbates cognitive dissonance. A tension arises

between the central government's policy objectives—

namely the "three stabilities" (stabilizing land prices,

housing prices, and market expectations)—and the

flexibility granted to local governments to

"implement city-specific policies," making it difficult

for investors to form consistent judgments. A typical

example is the divergent interpretation of "reasonable

demand"—whether home purchases for improvement

purposes fall within the scope of support often sparks

debate.

This dual ambiguity has driven investors to seek

information through informal channels. According to

a survey (DT Business Observer, 2025), over 60% of

small and medium-sized investors rely on WeChat

groups and short video platforms for policy

interpretation. However, distorted information spread

by self-media—such as "insider news on policy

relaxation" and "signals to buy at the bottom"—has

accelerated the formation of cognitive biases. As the

information environment deteriorates, investor

behavior becomes increasingly driven by emotion,

ultimately undermining the effectiveness of the

policy principle that "housing is for living in, not for

speculation."

4 CONCLUSION

4.1 Research Findings

The study reveals that investors' cognitive dissonance

during the implementation of the "housing is for

living, not for speculation" policy is primarily driven

by three mechanisms.

Policy ambiguity serves as the primary trigger: the

tension between the central government's "three

stability" objectives and the local governments'

flexible "city-specific policies" creates uncertainty.

The policy texts lack clear boundaries between

"supporting reasonable housing demand" and

"curbing speculation," as illustrated by ongoing

debates over the definition of improvement-oriented

home purchases. This ambiguity is further

exacerbated by inconsistent local implementation.

First-tier cities strictly implement relevant

regulations, but third-and fourth-tier cities have

hidden relaxation, which has led to continued

instability in market expectations.

Psychological effects exacerbate cognitive

conflicts, and small and medium-sized investors often

exhibit a "disposal effect", in which they hold loss-

making properties to avoid the pain of realizing losses.

"Loss aversion" causes fear of falling prices to

outweigh the desire for profit, which in turn triggers

Cognitive Dissonance Under Policy Shock: The Psychological Transmission Mechanism of China’s "Houses Are for Living in, Not for

Speculation" Policy on Investor Behavior

453

irrational behaviors such as refusing to sell. The

"anchoring effect" can cause investors to rely too

much on historical peak prices as a reference point

and ignore changes in market fundamentals.

The deterioration of the information environment

has played a catalytic role. More than 60% of small

and medium-sized investors rely on social media to

obtain scattered and often misleading interpretations,

such as the so-called "real estate speculation strategy",

and spread distorted information from the media,

such as "policy relaxation". Such rumors accelerate

the formation of cognitive bias.

Investors have shown a clear trend of stratification

and differentiation. Institutional investors such as

REITs, with the support of professional analysis,

focus on industrial parks and logistics assets with

stable cash flow, demonstrating strong resilience to

policy shocks. High-net-worth households are

accelerating their withdrawal from the real estate

sector while retaining high-quality properties in core

cities to fight inflation. In contrast, small and

medium-sized investors whose assets are highly

concentrated in real estate and lack financial

knowledge are particularly prone to irrational

behavior. They are easily influenced by psychological

bias and social media, leading to follow suit buying

or falling into a liquidity crisis.

This cognitive dissonance creates a negative

feedback loop between investor behavior and policies.

The disposal effect lengthens the holding cycle of

loss-making assets, loss aversion reduces the

willingness to accept price adjustments, and the

anchoring effect enhances price rigidity. These

factors work together to weaken policy transmission

and hinder reasonable adjustment of the real estate

market. Solving this dilemma requires targeted

intervention in the behavior of key groups, while

continuously improving the design of policy tools.

4.2 Policy Optimization and Behavioral

Adjustment Pathways

4.2.1 Short-Term Measures: Enhancing

Transparency and Managing

Expectations

In terms of information disclosure systems, the

United States has implemented new regulations in

recent years requiring identity disclosure in all-cash

real estate transactions. Under these rules,

transactions involving shell companies or legal

entities must report the buyer's true identity and

beneficial ownership information to relevant parties

to combat money laundering. These measures directly

increase market transparency and reduce the channels

for illicit funds to flow into the real estate sector.

China can learn from the Financial Crimes

Enforcement Network (FinCEN) model in the United

States and establish a unified national real estate

transaction database, requiring developers and

intermediaries to report the identity and source of

funds of full-time home buyers, especially for multi-

property holding by high-net-worth families.

In terms of managing policy expectations, the

United States regularly releases house price indices

and policy roadmap to help shape stable market

prospects, such as the Standard & Poor's/Case-Shiller

house price index and the Federal Reserve's forward-

looking guidance on interest rate decisions. China

could adopt a similar approach by regularly issuing a

"White Paper on Real Estate Policy" to clarify

regulatory objectives, outline the list of policy tools,

and specify implementation conditions, thereby

reducing arbitrary interventions by local governments.

4.2.2 Long Term: Policy Design in

Behavioral Economics

In the long-term evolution of policy tools, the concept

of psychological resilience assessment can be

incorporated by integrating investor sentiment

indicators into the policy-making process and

systematically embedding psychological factors—

such as the disposition effect and loss aversion—into

the analytical framework of the “housing is for living

in, not for speculation” policy.

One core strategy is to reconstruct the framework

of loss perception by requiring real estate platforms

and financial institutions to explicitly display the

“holding costs” of properties, such as monthly

interest payments and property management fees.

Through continuous visualization, this approach aims

to reduce the irrational overvaluation driven by the

endowment effect.

To counteract excessive anchoring to historically

high prices, the government should take the lead in

establishing and regularly publishing an authoritative

“Rational Housing Price Index.” This index should

incorporate rental yields, household income growth,

and regional economic fundamentals to provide an

objective benchmark based on long-term value,

thereby guiding the formation of reasonable price

expectations.

To address the widespread psychological

tendency of loss aversion, a pilot “Loss Offset

Subsidy” mechanism could be introduced. Individual

investors who sell properties at a loss could be

allowed to deduct a proportion of the net loss from

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their personal income tax. This measure would

transform the immediate “pain of book losses” into

future “tax relief,” thereby lowering the

psychological barrier to selling at a loss.

To directly address the disposition effect— the

tendency to sell winners and hold losers—real estate

agencies should be required to embed a “Holding

Cost Calculator” on property listing pages. This tool

should calculate various explicit costs, such as

interest and property management fees, as well as key

opportunity costs, such as other stable returns on

capital, to visualize the cumulative combined cost of

holding a losing property. This would encourage

investors to weigh all relevant factors to make more

rational decisions when deciding whether to hold or

sell.

4.2.3 Recommendations for Strategies to

Optimize Investor Behavior

Individual investors should have a deep

understanding and mastery of financial knowledge,

covering the basic dynamics of the real estate market,

the characteristics of various investment products,

and risk assessment methods. This knowledge allows

investors to maintain clear and rational thinking in a

complex market environment. Understanding

endowment effects and loss aversion is crucial to

formulating effective investment strategies and

appropriately responding to market policies. Through

education and policy intervention, investors can

understand these psychological deviations and adopt

more rational and balanced decision-making methods.

Therefore, investors can improve their financial

literacy by participating in relevant courses, reading

professional literature, or staying informed about

industry developments.

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