Financial Attention and Household Consumption Upgrading

Abstract

Based on data from the China Household Finance Survey (CHFS) conducted in 2019, this paper conducted an in-depth study on the impact and mechanism of financial attention on household consumption upgrading. The study found that an increase in financial attention can help to promote household consumption upgrading, and the result was still robust after using the instrumental variable method and substituting the explained variables. The mechanism analysis showed that financial attention can affect household consumption upgrading by influencing credit constraint and risk sharing. Heterogeneity analysis showed that the promotion effect of financial attention on consumption upgrading was significant in middle- and high-income households, high-financial-literacy households, and households living in first-tier cities.

1. Introduction

At present, with the rapid development of Internet technology, information has shown explosive exponential growth. However, faced with the unlimited increase in information supply, individual cognitive ability and the acquisition, understanding, and utilization of information are limited (Pashler & Johnson, 1998). Therefore, these abundant information resources cause a scarcity of attention (Simon, 1971). This limited attention leads to the allocation of cognitive resources between different tasks (Kahneman & Tversky, 1973) and may affect the economic behavior of households. It is particularly noteworthy that with the increase in income and the improvement in living standards, households’ demand for consumption is also increasing. In this process, increasing attention paid to economic and financial information (i.e., financial attention) provides more possibilities and options for household consumption upgrading. Therefore, the impact of household financial attention on consumption upgrading has become an issue worth studying.

Thus, a series of questions need to be considered. Does financial attention help to promote household consumption upgrading? What are the potential mechanisms by which financial attention affects household consumption upgrading? Will financial attention have a further impact on household consumption concepts, consumption patterns, and consumption confidence? How do we provide a useful reference for family consumption planning from the perspective of financial attention? Based on data from the China Household Finance Survey (CHFS) conducted in 2019, this study empirically examines the impact and mechanism of financial attention on household consumption. The possible marginal contribution of this study is mainly reflected in the following three aspects. Firstly, in terms of the research perspective, based on household micro-data, this study discusses the impact of financial attention on the quantity and quality of household consumption upgrading, identifies the specific impacts of financial attention on household consumption upgrading, and explores the differences in the impacts of financial attention on the specific consumption structure of households. The heterogeneity of income level, financial literacy, and regional differences are considered. Secondly, from the perspective of risk sharing, credit constraints, and other perspectives, this study studies the mechanism of the impact of financial attention on household consumption upgrading. Thirdly, in terms of practical guidance, based on the relevant influences and mechanism channels, some inspirations are put forward to provide some new directions for micro-research on the change and management of consumer groups. The significance of this study lies in that it can deepen research on the relationship between information overload and consumption behavior at the theoretical level, providing a scientific basis for households to optimize their consumption decisions and improve consumption quality at the practical level. It has important practical significance for promoting consumption upgrading and high-quality economic development.

2. Literature Review

2.1. Financial Attention

The concept of financial attention proposed in this study is closely related to the idea of limited attention put forward by Kahneman (1973). In fact, limited attention is closely related to many cognitive and decision-making biases in behavioral finance. For instance, the accessibility bias proposed by Tversky and Kahneman (1973), namely that due to the limitations in attention, memory, and information processing, investors tend to notice only part of the information available. There is also the framework bias proposed by Kahneman and Lovallo (1993), that is, that investors tend to analyze problems in a specific context, and their behaviors will be affected by the presentation mode of the information and its degree of dominance.

The concept of attention originates from psychology and occupies an important position in cognitive psychology. Wilhelm Wundt (1913) divided attention into immediate attention and delayed attention according to the time interval. Research has shown that people usually use immediate attention first to deal with important things, that is, individual attention is limited. With the deepening of research, behavioral finance has put forward some limited attention theoretical hypotheses, such as cognitive resource theory, salience theory, and frog-in-the-pan (FIP), for in-depth explorations of investors’ attention. Cognitive resource theory reveals the importance of attention as a scarce resource in decision making. In investment decision making, due to limited attention, it is difficult for investors to obtain and process effective information in a timely manner, thus making it difficult to reach optimal solutions (Kahneman & Tversky, 1973). Limited attention can lead investors to be influenced by cognitive bias and group behavior, prioritize the use of experience over irrational thinking, and fall into a frame-dependent thinking style (Ghysels et al., 2005). Traditional asset pricing theory assumes that investors are completely rational and use all information to judge risk assets, but research has found that their attention and processing ability are limited, resulting in excessive emphasis placed on prominent attributes and the neglect of others. Therefore, Bordalo et al. (2012) put forward prominent thinking, pointing out that due to cognitive limitations, investors are more likely to be exposed to risk. Decision makers will pay too much attention to the prominent attributes of risk assets and ignore other attributes, emphasizing the impacts of background dependence and attention allocation on investment decisions. Da et al. (2014) put forward the boiling frog theory, pointing out that investors are not sensitive to common and continuous information changes, but are more sensitive to sudden and drastic changes. This theory is analogous to the response of frogs to changes in water temperature. There is a threshold value for investors’ attention to information changes, and information changes below this threshold will not attract investors’ attention, while information changes above the threshold will attract investors’ attention.

In terms of attention description, most studies have measured investor attention, which can be divided into the following types. Firstly, direct proxy variables, such as the Google search index (Corwin & Coughenour, 2008; Da et al., 2011), stock bar posting volume (Sun et al., 2020), and other indicators can directly reflect the degree of investor attention. Secondly, indirect proxy variables, such as stock turnover (Gervais et al., 2001), stock turnover rate (Loh, 2010), advertising expenditure (Grullon et al., 2004), media coverage (Fang & Peress, 2009), certain events such as the daily limit of stock price (Seasholes & Wu, 2007), and the volume of stock weekend discussions (DellaVigna & Pollet, 2009), are important. The third is the use the information theory principle to characterize attention as a noise reduction process with entropy drop (Peng, 2005; Peng & Xiong, 2006), simplifying the model to signal de-noising to improve accuracy, so as to study financial contagion, optimal attention, price fluctuations, and delayed price responses to information (Van Nieuwerburgh & Veldkamp, 2010; Mondria & Quintana-Domeque, 2013; Kacperczyk et al., 2016; Hasler & Ornthanalai, 2018; Andrei & Hasler, 2020).

2.2. Financial Attention and Consumer Behavior

There are few direct studies on the impact of financial attention on household consumption behavior, but we can investigate the impacts of individual cognitive classification and cognitive resources on household consumption behavior from the perspective of mental account and financial literacy, respectively.

From the perspective of mental account, the research on the impact of cognitive classification on consumption behavior shows that mental account originates from Thaler’s (1980) interpretation of the sunk cost effect, in which people will take past inputs and present efforts as the total cost when making decisions, resulting in an unexpected influence on the psychological process of decision making. Psychological account is a classification made by consumers according to the source of wealth, consumption expenditure items, storage methods, etc., and this classification shows non-substitutability (Thaler, 1985). Since it was proposed, the theory of mental account has quickly become a research hotspot in the field of financial behavior decision making, obtaining abundant research results. Based on this theory, the behavioral portfolio theory (H. Shefrin & Statman, 2000) and the behavioral life cycle theory (H. M. Shefrin & Thaler, 1988) have been proposed, respectively, in the fields of financial investment and consumer behavior.

From the perspective of financial literacy, financial literacy represents an individual’s mastery of basic economic knowledge and financial concepts (Hung et al., 2009). Due to the complex process of financial investment decision making, investors need to extensively search for all kinds of information related to decision making and have the ability to process information (M. Van Rooij et al., 2011). Therefore, financial literacy can reflect individual cognitive resources, namely financial attention, to a certain extent. Murendo and Mutsonziwa (2017) found that financial literacy can improve the efficiency of household information acquisition and analysis. A large number of studies have shown that financial literacy is one of the important factors affecting household financial behavior, and a lack of financial literacy will lead to limited participation in the stock market (M. Van Rooij et al., 2011), the lack of a pension plan (M. C. Van Rooij et al., 2012), the use of informal credit (Klapper et al., 2013), and unreasonable debt behavior (Stango & Zinman, 2009). At the same time, some scholars have also discussed the impact of financial literacy on household savings, and found that financial literacy significantly improved the level of savings (Sayinzoga et al., 2016). In addition, some studies have shown that financial literacy is positively correlated with consumption level, and subjective financial literacy more strongly influences consumption in young people (Henager & Cude, 2016; Jappelli & Padula, 2017).

2.3. Literature Summary

Through reviewing the existing literature, it is found that there are few relevant studies directly focusing on financial attention and household consumption upgrading. There are many factors affecting household consumption upgrading, including some endogenous factors, such as family-level characteristics, the individual characteristics of household owners, information attention, etc., and some external factors, such as macroeconomic situation, tax level, wage policy, etc. In reality, there will be huge differences in household consumption upgrading due to these influencing factors. Households’ understanding and cognition regarding financial information are directly related to whether they can reasonably use financial information and knowledge to make investment and consumption decisions. Therefore, exploring the relationship between financial attention and household consumption upgrading can not only enrich the relevant research on the factors influencing household consumption upgrading, but also help to better explain the mechanism of the influence of financial attention on household consumption upgrading.

3. Theoretical Analysis and Research Hypothesis

3.1. The Direct Impact of Financial Attention on Household Consumption Upgrading

Based on the above literature research, it can be believed that the higher a household’s attention to economic and financial information, the more consumers form rational consumption cognition and pay attention to the quality and practicality of consumption, which helps to promote the upgrading of consumption. Therefore, the following research hypothesis is proposed.

H1: 

An increase in financial attention will promote consumption upgrading.

3.2. Indirect Effects of Financial Attention on Household Consumption Upgrading

3.2.1. Credit Constraint Effect

From the perspective of the influence of financial attention on credit behavior, information availability is the basis of economic decision making against the background of information asymmetry and incomplete information. In the second-hand goods market, people realized the importance of information (Akerlof & Burmeister, 1970). Subsequently, the issue of credit rationing was widely discussed (Stiglitz & Weiss, 1981). In the credit market, information has a fundamental impact on the borrowing decisions of capital demanders, including the choice of whether to borrow or not, the source of borrowing, the determination of the amount, and default and refinancing after successful borrowing.

From the perspective of the impact of credit constraints on household consumption behaviors, studies have found that credit constraints can significantly inhibit household consumption behaviors (Beaton, 2009; Oseni & Winters, 2009; Baker, 2018), especially households that lack liquid assets (Jappelli & Pistaferri, 2014). The ease of access to credit will affect the level of household consumption expenditure and debt, credit constraints will affect the consumption structure, leading households to choose between durable goods and consumption upgrading, and lifting credit constraints will increase durable goods expenditure (Leth-Petersen, 2010). Based on this, the following research hypothesis is proposed.

H2: 

Financial attention can affect household consumption upgrading by affecting household credit constraints.

3.2.2. Risk Sharing Effect

Considering the impact of financial attention on risk attitude, Bastounis et al. (2004) found that people who are not familiar with economic and financial knowledge are more likely to regard the stock market as a place for speculation and gambling.

From the perspective of the impact of risk attitude on household consumption behavior, individual consumption behavior is guided and promoted by risk cognition (Jevšnik et al., 2008). Risk attitudes have a significant impact on households’ economic and financial behaviors (Shim et al., 2009), such as insurance consumption decision making (Tawil, 2018), but the direction of this impact varies from country to country and insurance products. Such heterogeneity may be due to households’ risk tolerance (Cutler et al., 2008), patterns of behavior regarding the acceptance of new things (Cole et al., 2013), and religious beliefs (León & Pfeifer, 2017). Based on this, the following research hypothesis is proposed.

H3: 

Financial attention can affect household consumption upgrading by influencing commercial insurance participation intention.

3.2.3. Financial Market Participation Effect

From the perspective of the impact of financial attention on financial market participation, households with a deeper understanding of financial knowledge concepts are more likely to participate in financial markets and invest in stock markets (Almenberg & Dreber, 2015; Christelis et al., 2010; M. Van Rooij et al., 2011; Yoong, 2011).

From the perspective of the impact of financial market participation on household consumption behavior, Ando and Modigliani (1963) found that an increase in net asset value can promote consumption, that is, there is a wealth effect. Sousa (2008) confirmed that stock price fluctuations will affect the consumption expenditure of stockholders. Based on Swedish household data, Di Maggio et al. (2020) found that capital gains and dividends from financial assets have significant impacts on household consumption, and households with higher wealth levels have a lower marginal propensity to consume. Based on this, the following research hypothesis is proposed.

H4: 

Financial attention can influence household consumption upgrading by influencing household financial market participation.

4. Research Design

4.1. Model Setting

In order to explore the impact of financial attention on household consumption upgrading, this study sets the following model:

$$Daily\_consumptio{n}_i=\alpha +\beta Attentio{n}_i+\gamma X_i+{\epsilon }_i$$

(1)

wherein the explained variable $Daily\_consumptio{n}_i$ represents household consumption upgrading. $Attentio{n}_i$ is the core explanatory variable, indicating a household’s financial attention. $X$ is a series of control variables, mainly including gender, age, education, marital status, household registration, work, health, assets, income, and other household characteristic variables, as well as regional economic development level, regional price level, and other regional characteristic variables. $\epsilon$ is the random error term.

4.2. Variable Definition

4.2.1. Explained Variable

The explained variable is expressed by the proportion of household expenditure on food, clothing, housing, and transportation in the total consumption expenditure, that is, the proportion of daily consumption expenditure. When the proportion of daily consumption expenditure is relatively low, it means that the amount of household income used to meet basic needs is reduced, and more income may be used for other aspects of consumption, such as education, entertainment, tourism, medical care, etc., which is usually considered as the performance of consumption upgrading (Banks et al., 1997).

4.2.2. Explanatory Variable

Financial Attention

Financial attention is a quantitative indicator of a household’s attention to financial markets. When households pay more attention to information about financial markets, they are more likely to be knowledgeable about and participate in risky financial markets. In the 2019 CHFS, the question ‘How much do you pay attention to economic and financial information?’ was asked. The answer options to this question were graded on a five-point scale, ranging from ‘very concerned’ to ‘never concerned’. This study combines the first three levels of financial attention, namely ‘very concerned’, ‘very concerned’, and ‘general’, into one category and assigns a value of one, while ‘rarely concerned’ and ‘never concerned’ are combined into another category and assigned a value of zero. This treatment can more succinctly describe and analyze the degree of attention paid by household investors to the financial market.

Credit Constraints

This study is based on the question ‘Does your family need funds for production and operation?’ in the 2019 CHFS questionnaire. The answer to the question is used to define credit constraints. If the answer is ‘yes’, it is defined as the existence of credit constraints, and the value is one, otherwise it is zero.

Risk Sharing

This study selects whether households purchase commercial insurance to verify the risk sharing effect of financial attention on consumption upgrading. If households purchase commercial insurance, the value is one, otherwise it is zero.

Financial Market Participation

Participation in the financial market means whether a household is involved in the formal financial market, that is, whether it holds financial assets. According to the types of financial assets held by households in the CHFS 2019 questionnaire (cash/current deposit/time deposit/stocks/funds/bonds/financial derivatives/bank wealth management products/non-RMB assets/gold accounts), the more types of financial assets a household owns, the greater its participation in the financial market.

4.2.3. Control Variables

As for the selection of control variables, they are mainly selected from the characteristics of household head, household characteristics, and macro environment characteristics. Among them, household head characteristics include age, the square term of age, gender (male is one, female is zero), marital status (single, divorced, or widowed is zero, the remaining option of married is one), health status (healthy as one, the rest as zero), and whether you have a job (with a job as one, without a zero). Household characteristics include family population size, real estate conditions (owning a house as one, without a zero), total family income (logarithmic processing), total family assets (logarithmic processing), and so on. Macro environment characteristics include urban development level and consumer price index.

4.3. Data Source

The household finance data in this study come from the 2019 China Household Finance Survey (CHFS) database of the Southwestern University of Finance and Economics, which describes the financial behaviors of 34,643 households from 29 provinces (autonomous regions and municipalities directly under the Central Government) and 343 counties (districts and county-level cities) in China, which is typical. The data include the micro-information of households’ demographic characteristics, assets and liabilities, income and consumption, insurance and security, etc., comprehensively reflecting the basic financial situations of these households and also asking about their attention to economic and financial information in detail, providing good data support for this study on the impact of financial attention on consumption upgrading. All data were indentioned at the 5% level, and the descriptive statistical results of each variable are shown in

Table 1. Descriptive statistics of variables.

Variable Type	Variable Name	Variable Symbol	Observations	Mean	Standard Deviation	Min	Max
Explained variable	Proportion of daily consumption	Daily_consumption	32,359	0.683	0.201	0.009	7.656
Explanatory variable	Financial attention	Attention	32,359	0.244	0.429	0	1
	Credit constraints	Credit_constraint	32,359	0.126	0.332	0	1
	Risk sharing	Risk_sharing	32,359	0.101	0.301	0	1
	Financial market participation	Market_join	32,359	1.772	1.114	0	9
Control variable	Gender	Gender	32,359	0.756	0.429	0	1
	Age	Age	32,359	55.412	12.866	20	80
	Age squared	Age2	32,359	3236.058	1395.862	400	6400
	Educational level	Education	32,359	9.204	3.999	0	22
	Marital status	Married	32,359	0.858	0.349	0	1
	Working condition	Job	32,359	0.978	0.148	0	1
	Health status	Health	32,359	3.268	1.002	1	5
	Family size	Family_size	32,359	3.125	1.538	1	15
	House ownership	Housing	32,359	0.905	0.293	0	1
	Total household income	lnincome	32,359	10.608	1.376	5.635	13.273
	Total household asset	lnasset	32,359	12.768	1.67	7.889	16.058
	Level of regional economic development	lngdp	32,359	11.092	0.398	10.404	12.009
	Consumer price index	CPI	32,359	102.85	0.362	102.1	103.7

.

5. Empirical Results

5.1. OLS Regression

In this study, regression analysis was performed under the OLS model, and the results are shown in

Table 2. Results of baseline regression.

	(1)	(2)	(3)	(4)	(5)(IV)
VARIABLES	Daily_consumption	Daily_consumption	Daily_consumption	Daily_consumption	Daily_consumption
Attention	−0.008 ***	−0.014 ***	−0.016 ***	−0.015 ***	−0.046 ***
	(−2.87)	(−5.20)	(−6.15)	(−5.83)	(−4.16)
Gender		0.016 ***	0.026 ***	0.025 ***	0.025 ***
		(6.33)	(9.74)	(9.40)	(9.58)
Age		0.006 ***	0.007 ***	0.007 ***	0.007 ***
		(8.80)	(10.07)	(10.26)	(10.27)
Age2		−0.000 ***	−0.000 ***	−0.000 ***	−0.000 ***
		(−8.60)	(−10.68)	(−10.93)	(−10.94)
Education		−0.001 ***	−0.003 ***	−0.003 ***	−0.003 ***
		(−2.60)	(−8.95)	(−9.04)	(−6.88)
Married		−0.026 ***	−0.009 ***	−0.009 **	−0.009 ***
		(−7.75)	(−2.59)	(−2.44)	(−2.65)
Job		−0.016 **	−0.014 **	−0.014 **	−0.014 **
		(−2.32)	(−2.04)	(−2.01)	(−2.01)
Health		0.034 ***	0.032 ***	0.031 ***	0.032 ***
		(28.03)	(26.20)	(25.96)	(26.00)
Family_size			−0.016 ***	−0.016 ***	−0.016 ***
			(−18.13)	(−17.94)	(−17.94)
House			−0.041 ***	−0.037 ***	−0.038 ***
			(−10.21)	(−9.12)	(−9.30)
lnincome			0.003 ***	0.003 ***	0.003 ***
			(2.88)	(2.84)	(3.31)
lnasset			0.008 ***	0.007 ***	0.007 ***
			(8.17)	(6.69)	(7.34)
lngdp				0.016 ***	0.016 ***
				(5.35)	(5.20)
CPI				0.027 ***	0.026 ***
				(9.23)	(8.80)
Constant	0.685 ***	0.451 ***	0.408 ***	−2.584 ***	−2.493 ***
	(537.21)	(22.60)	(18.91)	(−8.27)	(−7.90)
Observations	32,359	32,359	32,359	32,359	32,358
R-squared	0.000	0.030	0.046	0.049	0.045

Note: T-statistic value in parentheses, *** p < 0.01, ** p < 0.05.

. From column 1 to column 3 of Table 2, it can be seen that with the gradual addition of individual-level characteristic variables, household-level characteristic variables, and regional characteristic variables, the coefficient of financial attention is significantly negative and is significant at the level of 1%, indicating that after considering all influencing factors, financial attention has a significant positive impact on household consumption upgrading, thus verifying hypothesis H1. The possible explanation is that, on the one hand, households can better understand market dynamics, financial products, and their risks by paying attention to financial information, and households with high financial attention are more sensitive to market dynamics and can grasp market trends and opportunities more accurately, so as to make more appropriate consumption decisions. On the other hand, access to financial information also helps households to update their consumption concepts, such as advocating rational consumption and attaching importance to consumption quality, and the updating of these concepts will encourage households to upgrade their consumption. The attention paid to information has a significant impact on the choices of financial behaviors (Hong et al., 2004). Information asymmetry requires households to bear additional information costs, thereby affecting their behavioral decisions (Merton, 1987). Due to the inequality in information acquisition, there are significant differences in financial behaviors among households (Peress, 2004). After testing, the variance inflation factor (VIF) is 1.31, indicating that there is no multicollinearity.

5.2. Robustness Test

5.2.1. Endogenetic Analysis

In order to solve the potential endogeneity problem, the median financial attention in the community, excluding the household itself, is selected as the instrumental variable. The selection of instrumental variables needs to satisfy the conditions of correlation and exogeneity. On the one hand, the financial attention of households themselves will increase, to a certain extent, due to an increase in the financial attention of households in the community where they are located, meeting the requirements of instrumental variable correlation. On the other hand, the financial attention of households in the community, excluding the household itself, struggles to directly affect the income level of the household itself, meeting the exogeneity requirement of the instrumental variable. Therefore, it is a relatively ideal instrumental variable. The estimated results of the instrumental variables are shown in column 5 of Table 2. According to the estimated results, there is a significant negative correlation between financial attention and the proportion of daily consumption, indicating that financial attention promotes consumption upgrading. The Durbin–Wu–Hausman test is further conducted to see whether it is really an endogenous variable. If the test passes, it indicates the existence of endogenous variables. The test results show that the F value is 8.6916 and the p value is 0.000, which significantly rejects the null hypothesis. Furthermore, the results of the weak instrumental variable test show that the minimum eigenvalue is 1981.67, greater than 10, which passes the weak recognition test, indicating that the use of instrumental variable estimation is appropriate. Therefore, after alleviating the endogenous problem, financial attention can still promote household consumption upgrading.

5.2.2. Robustness Discussion

(1)

Financial practitioners are excluded

Compared with households who are not engaged in the financial industry, financial practitioners have been trained in specialized financial literacy, and they pay more attention to financial information, which may cause estimation bias. Therefore, excluding the sampled households whose heads are engaged in the financial industry, the estimated results are shown in column 1 of

Table 3. Robustness test.

	(1)	(2)
VARIABLES	Daily_consumption	Daily_consumption
Attention	−0.046 ***	0.057 ***
	(−4.09)	(12.86)
Gender	0.025 ***	−0.014 ***
	(9.50)	(−11.73)
Age	0.007 ***	−0.004 ***
	(10.25)	(−15.88)
Age2	−0.000 ***	0.000 ***
	(−10.92)	(14.95)
Education	−0.003 ***	0.002 ***
	(−6.79)	(14.89)
Married	−0.009 ***	−0.004 ***
	(−2.67)	(−2.63)
Job	−0.013 *	0.006 **
	(−1.88)	(1.96)
Health	0.032 ***	0.003 ***
	(26.02)	(6.97)
Family_size	−0.016 ***	−0.004 ***
	(−17.83)	(−15.05)
House	−0.037 ***	−0.003 *
	(−9.03)	(−1.92)
lnincome	0.003 ***	0.005 ***
	(3.27)	(13.51)
lnasset	0.007 ***	0.006 ***
	(7.34)	(18.38)
lngdp	0.016 ***	0.004 ***
	(5.19)	(3.41)
CPI	0.027 ***	−0.007 ***
	(8.79)	(−5.55)
Constant	−2.508 ***	0.681 ***
	(−7.91)	(5.54)
Observations	32,102	32,358
R-squared	0.045	0.129

Note: T-statistic value in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

. The influence coefficient of financial attention on daily consumption expenditure is still significantly negative, which is consistent with the previous estimated results and proves the robustness of the results.

(2)

Replace the explained variable

Total household consumption is divided into survival consumption, development consumption, and enjoyment consumption, among which survival consumption includes food consumption, clothing consumption, and housing consumption, development consumption includes medical and healthcare consumption, transportation and communication consumption, and home equipment and services consumption, and enjoyment consumption includes entertainment consumption and other consumption. Development and enjoyment consumption are used to replace the original explained variables, and the results are shown in column 2 of Table 3. The influence of financial attention on development and enjoyment consumption is significantly positive. This is consistent with the previous estimation results, which proves the robustness of the results.

5.3. Mechanism Analysis

Credit_constraint was substituted into the regression model, and the test results are shown in column 1 of

Table 4. Mechanism analysis.

	(1)	(2)	(3)
VARIABLES	Daily_consumption	Daily_consumption	Daily_consumption
Attention	−0.055 ***	−0.048 ***	−0.044 ***
	(−4.37)	(−3.81)	(−3.72)
Credit_constraint	−0.039 ***
	(−7.83)
Attention×Credit_constraint	0.061 ***
	(4.45)
Risk_sharing		−0.020 ***
		(−4.59)
Attention×Risk_sharing		0.024 *
		(1.74)
Market_join			−0.002
			(−1.33)
Attention×Market_join			−0.002
			(−0.44)
Gender	0.025 ***	0.025 ***	0.025 ***
	(9.66)	(9.36)	(9.47)
Age	0.007 ***	0.007 ***	0.007 ***
	(10.25)	(10.30)	(10.28)
Age2	−0.000 ***	−0.000 ***	−0.000 ***
	(−11.08)	(−11.07)	(−10.95)
Education	−0.003 ***	−0.003 ***	−0.003 ***
	(−6.93)	(−6.90)	(−6.91)
Married	−0.010 ***	−0.009 ***	−0.009 ***
	(−2.71)	(−2.62)	(−2.63)
Job	−0.014 **	−0.013 *	−0.014 **
	(−2.05)	(−1.96)	(−1.98)
Health	0.031 ***	0.032 ***	0.032 ***
	(25.62)	(26.03)	(26.05)
Family_size	−0.016 ***	−0.016 ***	−0.016 ***
	(−17.41)	(−17.90)	(−17.56)
House	−0.039 ***	−0.038 ***	−0.039 ***
	(−9.50)	(−9.40)	(−9.43)
lnincome	0.003 ***	0.004 ***	0.004 ***
	(3.15)	(3.50)	(3.50)
lnasset	0.007 ***	0.008 ***	0.008 ***
	(7.30)	(7.63)	(7.61)
lngdp	0.015 ***	0.016 ***	0.016 ***
	(4.82)	(5.09)	(5.38)
CPI	0.026 ***	0.027 ***	0.027 ***
	(8.66)	(8.87)	(8.85)
Constant	−2.430 ***	−2.516 ***	−2.529 ***
	(−7.67)	(−7.98)	(−7.98)
Observations	32,358	32,358	32,358
R-squared	0.046	0.045	0.045

Note: T-statistic value in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

. It can be seen from the regression results that the interaction term ($Attentio{n}_i\ast Credit\_constrain{t}_i$) coefficient is significantly positive. That is, financial attention did not promote consumption upgrading by easing household credit constraints, but inhibited consumption upgrading. On the one hand, households with high credit constraints usually lack credit history, with insufficient collateral or income proof. Even if credit constraints are eased to a certain extent, their consumption power will be limited and they may not be able to carry out some development and enjoyment consumption. On the other hand, in the context of increased financial attention, households may be more aware of risks and consequences. If households are concerned about the risks that excessive borrowing may bring, such as repayment pressure, credit problems, etc., they may still choose to keep their debt levels low, thus restraining consumption escalation.

Risk_sharing was substituted into the regression model, and the test results are shown in column 2 of Table 4. As can be seen from the regression results, an increase in financial attention can still help to reduce the proportion of households’ daily consumption and a reduction in risk uncertainty can also help to reduce the proportion of households’ daily consumption expenditure, but the coefficient of the interaction term ($Attentio{n}_i*Risk\_sharin{g}_i$) is significantly positive. That is, financial attention did not promote consumption upgrading by reducing risk uncertainty, but also inhibited consumption upgrading. The reason is that when households pay more attention to financial risks, they may be too cautious about their consumption behavior and worry too much about the possible consequences of economic fluctuations and market risks. This excessive caution may lead households to remain conservative in choosing consumption upgrading, even though they avoid risks by participating in commercial insurance.

Financial market participation (Market_join) was substituted into the regression model, and the test results are shown in column 3 of Table 4. As can be seen from the regression results, the coefficient of interaction term ($Attentio{n}_i*Market\_joi{n}_i$) is not significant, that is, the financial participation effect of financial attention promoting consumption upgrading is weak.

5.4. Heterogeneity Analysis

This study further examines the impact of financial attention on household consumption upgrading under different household income levels. In this study, all households are sorted by income from low to high, and households in the top 20% will be defined as high-income households, households in the bottom 20% of income level will be divided into low-income households, and the rest are middle-income households. Group regression is performed, and the specific regression results are shown in

Table 5. Influence of financial attention on consumption upgrading of households with different incomes.

VARIABLES	(1)	(2)	(3)
	Daily_consumption (Low-Income Group)	Daily_consumption (Middle-Income Group)	Daily_consumption (High-Income Group)
Attention	0.031	−0.044 ***	−0.070 **
	(1.18)	(−3.98)	(−2.56)
Gender	0.031 ***	0.025 ***	0.020 ***
	(4.80)	(9.42)	(3.16)
Age	0.006 ***	0.007 ***	0.005 ***
	(3.77)	(10.28)	(2.82)
Age2	−0.000 ***	−0.000 ***	−0.000 ***
	(−4.17)	(−10.95)	(−3.19)
Education	−0.001	−0.003 ***	−0.005 ***
	(−0.77)	(−6.44)	(−3.72)
Married	−0.029 ***	−0.009 **	0.008
	(−4.26)	(−2.49)	(0.65)
Job	−0.026	−0.013 *	0.019
	(−1.51)	(−1.92)	(1.01)
Health	0.040 ***	0.032 ***	0.017 ***
	(15.34)	(26.34)	(4.66)
Family_size	−0.022 ***	−0.016 ***	−0.009 ***
	(−10.24)	(−17.64)	(−2.90)
House	−0.030 ***	−0.040 ***	−0.048 ***
	(−3.35)	(−9.79)	(−4.54)
lnasset	0.006 ***	0.008 ***	0.011 ***
	(2.86)	(8.39)	(3.00)
CPI	0.012	0.017 ***	0.008
	(1.58)	(5.50)	(1.13)
lngdp	0.021 ***	0.026 ***	0.021 ***
	(3.11)	(8.68)	(2.64)
Constant	−1.876 ***	−2.444 ***	−1.754 **
	(−2.65)	(−7.76)	(−2.08)
Observations	6471	32,358	6470
R-squared	0.073	0.045	0.009

Note: T-statistic value in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

. The results show that the promotion effect of financial attention on household consumption upgrading is significant in middle- and high-income households, but not in low-income households. A possible explanation is that the economic foundation of middle- and high-income households is relatively stable, and such households are more likely to pay attention to the dynamics and changes in the financial market on the basis of their spare power, realizing the appreciation of wealth through financial management and investment, so they have more funds for consumption upgrading and improving their quality of life. In contrast, the funds of low-income households are mainly used to meet the basic needs of life, and they may face more economic pressure and uncertainty. Even if these households pay attention to financial information, its promotion effect on consumption upgrading may be relatively limited due to the limitation of their income level.

Similarly, this study further examines the impact of financial attention on household consumption upgrading under different financial literacy levels. Financial literacy was first proposed by Noctor et al. (1992). The Organization for Economic Co-operation and Development (OECD, 2016) refers to it as the ability to recognize, master, and apply financial concepts and risks. It can help individuals or society to make effective decisions in different financial environments. Lusardi and Mitchell (2011, 2014) defined financial literacy as the ability to master economic information and make decisions based on it regarding finance, debt, pension plans, etc. From this, it can be known that financial literacy is a special kind of human capital, which serves as an ability to master and apply financial knowledge.

This paper uses the factor analysis method to construct indicators for measuring the financial literacy of households. In the 2019 CHFS questionnaire, four questions were used to assess the financial literacy of households. These four questions are as follows, respectively: “Q1: Suppose the annual interest rate of the bank is 4%. If CNY 100 is deposited as a fixed deposit for one year, what will be the principal and interest obtained after one year?”. “Q2: Suppose the annual interest rate of the bank is 5% and the inflation rate is 8% per year. How many things can be bought after depositing CNY 100 in the bank for one year?”. “Q3: Which do you think is riskier, stocks on the main board or those on the growth enterprise market?”. “Q4: In your opinion, which one is riskier, equity-oriented funds or bond-oriented funds?”. Q1 and Q2 examined a household’s ability to calculate interest rates and inflation rates, that is, their level of objective financial literacy. Q3 and Q4 mainly measure the subjective financial literacy of a household. The KMO test results indicated that factor analysis was suitable. Ultimately, one factor was retained, representing the overall financial literacy of the household.

In this study, financial literacy is ranked from low to high income, and households within the top 20% financial literacy level are defined as having a high financial literacy, households within the bottom 40% financial literacy level are divided into low-financial-literacy households, and the rest are households with a medium financial literacy. Group regression is performed, and the specific regression results are shown in

Table 6. Influence of financial attention on consumption upgrading of households with different financial literacy levels.

VARIABLES	(1)	(2)	(3)
	Daily_consumption (Low Financial Literacy Group)	Daily_consumption (Middle Financial Literacy Group)	Daily_consumption (High Financial Literacy Group)
Attention	−0.019	−0.019	−0.069 ***
	(−0.78)	(−0.78)	(−3.07)
Gender	0.031 ***	0.031 ***	0.028 ***
	(7.23)	(7.23)	(5.03)
Age	0.007 ***	0.007 ***	0.003 **
	(4.73)	(4.73)	(2.26)
Age2	−0.000 ***	−0.000 ***	−0.000 ***
	(−5.45)	(−5.45)	(−2.66)
Education	−0.001 ***	−0.001 ***	−0.004 ***
	(−2.59)	(−2.59)	(−3.84)
Married	−0.019 ***	−0.019 ***	0.000
	(−3.72)	(−3.72)	(0.02)
Job	−0.027 **	−0.027 **	−0.019
	(−2.45)	(−2.45)	(−1.18)
Health	0.035 ***	0.035 ***	0.023 ***
	(19.13)	(19.13)	(6.80)
Family_size	−0.019 ***	−0.019 ***	−0.012 ***
	(−14.98)	(−14.98)	(−3.25)
House	−0.038 ***	−0.038 ***	−0.039 ***
	(−5.80)	(−5.80)	(−4.32)
lnincome	0.005 ***	0.005 ***	−0.002
	(3.33)	(3.33)	(−0.92)
lnasset	0.009 ***	0.009 ***	0.007 ***
	(5.88)	(5.88)	(2.79)
CPI	0.024 ***	0.024 ***	0.015 **
	(4.76)	(4.76)	(2.37)
lngdp	0.022 ***	0.022 ***	0.021 ***
	(4.80)	(4.80)	(3.31)
Constant	−2.139 ***	−2.139 ***	−1.764 ***
	(−4.44)	(−4.44)	(−2.58)
Observations	13,615	13,615	6335
R-squared	0.069	0.069	0.006

Note: T-statistic value in parentheses, *** p < 0.01, ** p < 0.05.

. The results show that the promotion effect of financial attention on household consumption upgrading is significant in households with a high financial literacy, but not obvious in households with a middle and low income. The reason for this effect may be that households with a high financial literacy usually have a stronger financial understanding ability, which enables them to understand and use financial products and services more effectively, so as to promote the appreciation of wealth through reasonable asset allocation and investment decisions, providing greater space for consumption upgrading. Households with a low and medium financial literacy may have difficulty understanding and utilizing complex financial products and services due to their lack of financial literacy.

Similarly, this study further examines the impact of financial attention on household consumption upgrading under different urban development levels. CHFS divided the geographic information of the samples into first-tier cities and second-tier cities. The first-tier cities included Shanghai, Beijing, Shenzhen, Guangzhou, Chengdu, Hangzhou, Chongqing, Xi ‘an, Suzhou, Wuhan, Nanjing, Tianjin, Zhengzhou, Changsha, Dongguan, Foshan, Ningbo, Qingdao, and Shenyang. Second-tier cities included Hefei, Kunming, Wuxi, Xiamen, Jinan, Fuzhou, Wenzhou, Dalian, Harbin, Changchun, Quanzhou, Shijiazhuang, Nanning, Jinhua, Guiyang, Nanchang, Jiaxing, Zhuhai, Nantong, Huizhou, Taiyuan, Zhongshan, Xuzhou, Shaoxing, Changzhou, Taizhou, Yantai, Lanzhou, Weifang, and Linyi. The results of grouping regression are shown in

Table 7. Influence of financial attention on household consumption upgrading in different cities.

VARIABLES	(1)	(2)
	Daily_consumption (First-Tier Cities)	Daily_consumption (Second-Tier Cities)
Attention	−0.047 **	0.020
	(−2.08)	(0.61)
Gender	0.019 ***	0.022 ***
	(4.26)	(3.39)
Age	0.008 ***	0.007 ***
	(6.84)	(4.42)
Age2	−0.000 ***	−0.000 ***
	(−7.29)	(−4.77)
Education	−0.004 ***	−0.006 ***
	(−4.53)	(−4.74)
Married	0.004	0.002
	(0.61)	(0.20)
Job	0.004	−0.011
	(0.29)	(−0.62)
Health	0.028 ***	0.034 ***
	(10.74)	(10.34)
Family_size	−0.015 ***	−0.016 ***
	(−5.14)	(−6.98)
House	−0.042 ***	−0.034 ***
	(−5.80)	(−3.10)
lnincome	−0.000	0.005 *
	(−0.13)	(1.91)
lnasset	0.005 **	0.003
	(2.54)	(1.07)
CPI	0.019 ***	0.057 ***
	(2.79)	(7.75)
lngdp	0.040 ***	−0.056 ***
	(5.47)	(−5.11)
Constant	−3.855 ***	5.548 ***
	(−4.87)	(5.00)
Observations	8966	4757
R-squared	0.033	0.059

Note: T-statistic value in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1.

. The results show that the promotion effect of financial attention on household consumption upgrading is significant in households sampled from first-tier cities, while the promotion effect is not obvious in the sample of households from second-tier cities. The reason for this effect may be that, from the perspective of households’ income level, households in first-tier cities generally have a higher income level, stronger consumption power, and stronger demand for financial services. An improvement in financial attention can better meet these needs and promote consumption upgrading. Although the income level of households in second-tier cities is also increasing, it may be relatively limited, and the degree of satisfaction with financial services is relatively low, so financial attention plays a relatively small role in promoting consumption upgrading. From the perspective of financial popularity and service level, first-tier cities have a higher financial popularity and households have a deeper understanding of financial literacy and services. An improvement in financial attention can better guide households to conduct financial management and consumption, promoting consumption upgrading. However, the financial popularity and services available in second-tier cities may be relatively insufficient, resulting in the role played by financial attention in promoting consumption upgrading not being obvious.

6. Conclusions

Based on the data from the China Household Finance Survey (CHFS) conducted in 2019, this paper conducted an in-depth study on the impact and mechanism of financial attention on household consumption upgrading. The findings are as follows.

Firstly, this research confirms that an increase in financial attention has a significant promoting effect on the upgrading of household consumption. This conclusion remains robust after using the instrumental variable method and replacing the explained variable. Increased attention to finance enables households to have a deeper understanding of the financial market and be able to grasp market trends and opportunities more accurately. This information advantage provides more possibilities and choices for consumption decisions. Meanwhile, increased attention to finance also helps households to update consumption concepts, advocate rational consumption, and attach importance to consumption quality. To a certain extent, this promotes households to shift from meeting basic living needs to pursuing a higher quality of life, facilitating consumption upgrading.

Secondly, the research reveals the mechanism of the effect of financial attention on the upgrading of household consumption. From the perspective of credit constraints, although an increase in financial attention can help to alleviate credit constraints, the alleviation of credit constraints does not necessarily directly promote the upgrading of household consumption. Households with higher credit constraints often lack credit records, collateral, or income proof. Even if credit constraints are eased, their consumption capacity is still limited and it is difficult for them to engage in development–enjoyment consumption. On the other hand, with an increase in financial attention, households have a clearer understanding of borrowing risks and may choose to maintain a low debt level to avoid repayment pressure and credit problems. This cautious attitude, to a certain extent, curates consumption upgrading. In terms of risk sharing, although an increase in financial attention helps to reduce risk uncertainty, excessive focus on financial risks may lead households to be overly cautious when consuming, worrying about the consequences brought about by economic fluctuations and market risks. Even if they avoid some risks by participating in commercial insurance, they may still be conservative in making decisions on consumption upgrading. As for financial market participation, the research finds that the effect of financial attention on the financial market participation of household consumption upgrading is relatively weak, which indicates that the potential of financial market participation in promoting household consumption upgrading has not been fully realized.

Finally, the heterogeneity analysis indicates that the promotion effect of financial attention on household consumption upgrading varies significantly among households with different characteristics. In terms of income level, for middle- and high-income households, an increase in financial attention can significantly promote consumption upgrading. These households have a relatively stable economic foundation and are more likely to pay attention to the dynamics of the financial market. They can achieve wealth appreciation through financial management and investment, and, thus, have more funds for consumption upgrading. However, for low-income households, since their funds are mainly used to meet basic living needs, even if they pay attention to financial information, its promotion effect on consumption upgrading is relatively limited. In terms of financial literacy, households with a high financial literacy, due to their stronger financial knowledge and comprehension ability, can make more effective use of financial products and services. In contrast, households with a medium and low financial literacy, due to their lack of financial knowledge, may have difficulty in understanding and utilizing complex financial products and services, and their consumption behaviors are less influenced by financial attention. In terms of regional differences, financial attention has a more significant promotion effect on consumption upgrading in household samples from first-tier cities. Residents in first-tier cities have a relatively high income level and strong consumption capacity, and their demand for financial services is more vigorous. Increased attention to finance can better meet these demands and promote consumption upgrading. Meanwhile, the financial penetration rate in first-tier cities is high, and residents have a deeper understanding of financial knowledge and services. An increase in financial attention can more effectively guide residents to manage their finances and consume, promoting consumption upgrading. In second-tier cities, due to the relatively limited income level of residents, the popularization degree and service levels of finance are relatively insufficient, and the promotion effect of financial attention on consumption upgrading is relatively small.

Overall, this study delves deeply into the impact of financial attention on household consumption upgrading. At the same time, it reveals the heterogeneous effects occurring under different household characteristics, providing useful references and inspiration for promoting household consumption upgrading.