Frontiers in Business, Economics and Management ISSN: 2766-824X | Vol. 8, No. 3, 2023 126 The Influence of House Price on The Average Age of First Marriage in China Zunbo Ma, Luyao Ma, Zhiyi Yang, Yibo Wang, Zige Wang* Henan University, Zhengzhou, Henan Province 475000, China * Corresponding author Abstract: With the rapid development of economy, the domestic environment is characterized by the rapid rise of housing prices and the encouragement of marriage and childbearing by policies, and the age of first marriage in China has also changed. Based on the data from 1998 to 2021, this paper builds a model to measure the effect of the average house price in China on the age of first marriage, and supplements the control variables such as the population difference between men and women, the enrollment rate of senior high school and the expenditure of maternity insurance fund to describe the changes of the age of first marriage in China in detail. Through empirical analysis, we come to the conclusion that the high average house price has significantly delayed the age of first marriage in China. Accordingly, this study suggests that the state should promote relevant housing policies to curb the rapid growth trend of housing prices while ensuring the rigid demand of residents' housing. Keywords: Average house price in China, Average age of first marriage, Maternity insurance fund expenditure, Population difference between male and female, High school enrollment rate. 1. Introduction In 2021, the Political Bureau of the Communist Party of China (CPC) Central Committee held a meeting to further optimize the birth policy to deal with China's demographic problems. In order to adapt to the general trend of the times, the "letting go of the three children" called by many parties has officially become a domestic marriage and childbearing policy. In addition, there are endless calls for lowering the legal age of marriage in the two sessions, and the overall domestic policy environment is biased towards encouraging marriage and childbirth. However, the ensuing controversy can not be ignored. On the one hand, with the in-depth development of reform and opening up, China has achieved an all-round well-off society in 2020. With the rapid development of economy, people's concept of marriage and childbearing has changed, and people generally adopt a more cautious attitude towards marriage. On the other hand, the rapid economic development has also caused the real estate prices to soar, far exceeding the economic acceptance of most people. However, in China's marriage culture, marriage and real estate are often inseparable. The reason why the house plays such an important role in marriage is that it carries the sense of belonging and security of family members. Moreover, the house is an important symbol standard to convey the man's assets and social status (Fang Li and Tian Chuanhao, 2016) [1]. These factors determine that the influence of domestic housing prices on marriage is very important. However, marriage is not only a "life event" in China people's concept, but also a life stage choice under the influence of parents and other relatives. Choosing to enter marriage at marriageable age has always been the mainstream culture of marriage in China. However, when the increase of housing prices and other factors exceeds the economic ability of young people, it will inevitably have a certain impact on the age of first marriage. In view of this, the relevant research focuses at home and abroad are different. In China, theoretical research is more important, while in foreign countries, the relationship between marriage rate and housing price is mainly studied from a macro perspective, both theoretically and empirically. However, on the whole, scholars have not reached a consistent conclusion on how housing prices affect the average age of first marriage in China. Based on the background of policy environment, domestic economic development, rising house prices and changing concept of marriage and childbearing, this paper uses representative data and econometric models from 1998 to 2021 to analyze how house prices affect the average age of first marriage in China. The significance of this study is not only to make up for the vacancy of domestic empirical research, in order to draw a more clear conclusion; I hope to provide relevant research support for domestic people's livelihood issues, provide reliable suggestions for domestic marriage issues, and make modest contributions and efforts to build a socialist modern power in an all-round way. 2. Literature Review Scholars at home and abroad have rich research on the factors influencing the delay of first marriage, which mainly focus on income, population difference between men and women, women's economic status and education level. And some scholars focus on the relationship between marriage and housing prices. With regard to the research on the influence of house price on the first marriage decision, foreign countries mainly study the relationship between marriage rate and house price from a macro perspective. Theoretically, Brown (1980) believes that housing is the key factor for newly formed families to enter marriage, and rising house prices will bring about an increase in the cost of marriage, reducing people's demand for marriage to some extent [2]. In addition, Becker (1988) and others founded family economics, and used the theory of maximizing family utility to deeply discuss the emergence of marriage and the formation of family, and thought that house price was an important factor affecting the formation of family [3]. On the empirical side, Bowmaker and Emerson (2015) found that the higher the ratio of house price 127 to income, the lower the marriage rate [4] based on the data of 2450 cities in the United States from 1970 to 1999. Gholipour and Farzanegan, based on the data of Iranian provinces from 2002 to 2010, found that there was a negative correlation between housing expenditure and marriage rate [5]. Domestic research on the influence of house price on first marriage mainly starts from the perspectives of social concept, population difference between men and women and education level, and only a few scholars focus on the relationship between rising house price and marriage rate, which may only indirectly involve the influence of house price on first marriage age. Theoretically, Chen Binkai and Yang Rudai (2013) found that the rising cost of marriage is the direct reason for the delay of first marriage in China. They think that the income of young people is relatively unstable, and high housing prices will increase the family savings rate [6]. On the empirical side, Hong Caini (2012), based on the provincial panel data of China from 2004 to 2008, found that for every 1% increase in housing prices, the first marriage rate decreased by about 0.02 thousandths [7]. In addition, Zeng Zhen (2018) used PCSE method and provincial panel data of 31 provinces from 2001 to 2015, and found that there is an inverted U-shaped curve relationship between house prices and the first marriage rate [8]. Liu Jinshan (2022), based on the data of CGSS 2017, used multiple linear regression model to test that house prices have a significant delay effect on the first marriage decision of the marriageable population [9]. By combing the above literature, we can find that there have been studies to explore the influencing factors of the first marriage decision, and theoretically analyze the influence of house prices on the first marriage decision, which laid an important foundation for our research. However, at present, there is still a lack of empirical analysis and research on housing prices and first marriage variables such as first marriage age in academic circles. Most of the research focuses on the role and changes of factors such as education, employment and good economic foundation of both men and women, while ignoring the impact of macro events on marriage decision-making, such as housing prices as a prominent phenomenon of social and economic transformation. Especially in the context of soaring housing prices in recent ten years, there are even fewer empirical studies using representative samples and data. Based on the existing research results, most scholars believe that the rise in housing prices has a delaying effect on China's first marriage decision. However, based on different databases, data years and corresponding model methods, there is no unified conclusion about the impact of housing prices on the average age of first marriage in China. Therefore, this study uses representative data and econometric models from 1998 to 2021 to analyze how housing prices affect the average age of first marriage in China. 3. Theoretical Analysis and Research Hypothesis Wang Jie (2021) found that for China people, buying a house is not only for living, but also a factor to maintain the stability of marriage [10]. In 1998, China abolished the housing distribution system and implemented the reform of commercial housing. Since then, the housing prices in China have been rising (Han Libin and Lu Ming, 2018). Some young people who intend to get married are often blocked by their families because they can't afford the high housing prices, and finally fail to get married [11]. Through the research of Chen Binkai and Yang Rudai (2013), it is found that buying a house needs to spend most of the savings of both families, especially the husband's family, and makes young people bear huge debts, which shows that it has a direct impact on delaying the first marriage. Based on this, we put forward the hypothesis: Hypothesis 1. The increase of average house price in China has a significant impact on the increase of the age of first marriage. 4. Models, Variables and Data Section 1 Model setting The author draws lessons from the existing research practices, and uses OLS method model to analyze whether the house price will affect the individual's first marriage age and the direction and intensity of the influence. By minimizing the sum of squares of errors, the author finds relevant data to match the best function model and establishes the following multiple linear regression model： π‘Œ 𝛽0 𝛽1 βˆ— π‘ƒπ‘Ÿπ‘–π‘π‘’ 𝛽2 βˆ— πΈπ‘‘π‘’π‘π‘Žπ‘‘π‘–π‘œπ‘› 𝛽3 βˆ— πΊπ‘’π‘›π‘‘π‘’π‘Ÿ 𝛽4 βˆ— πΌπ‘›π‘ π‘’π‘Ÿπ‘Žπ‘›π‘π‘’ πœ‡ Section 2 Variables and data sources This study involves three kinds of variable data, namely explained variable, explained variable and controlled variable. First of all, the explained variable (Y) represents the age of the first marriage population in China every year. Secondly, considering the differences and differences in the level and rate of changes in house Prices among different regions and between urban and rural areas, this paper adopts the unified national standard, namely the average house price in China, as the core explanatory variable. Finally, the control variables fall into the following two categories: first, the control variables found in the literature that are related to the age of first marriage, including Education, but because the education level is difficult to measure, we choose the high school enrollment rate as an index to quantify the education level; Second, the control variables that may be related to the age of first marriage are considered for practical reasons, such as Gender and maternity Insurance fund expenditure. Zhu Zhou (2022) believes that the development of higher education objectively promotes the rise of the age of first marriage and first childbearing; Therefore, we finally adopted the high school enrollment rate as an indicator of our quantitative education level [12]. The population difference between men and women is also a very important factor to measure. Liu Zhongyi (2023) thinks that in a given marriage market, the imbalance of the population difference between men and women of marriageable age will lead to marriage squeeze, which will further increase the average age of first marriage in China [13]. In addition, the expenditure of maternity insurance fund will also have an impact on the age of first marriage, because the economic pressure of childbirth will be objectively transmitted to the age of first marriage. For example, the high cost of raising children will burden families, and the opportunity cost of childbirth is high (including the change of work, the balance between career and family, etc.). Therefore, the investment of maternity fund will objectively promote the decline of the age of first marriage. According to the availability and timeliness of data, this 128 paper selects 1998-2021 as the data period. The data mainly comes from the Statistical Yearbook of China. Of course, it should be noted that there are many specific force majeure factors that lead to the lack of data. In this paper, the data is completed by stata using linear interpolation method. Table 2. Primary data Table 3. Filled data Note: The enrollment stata in 2019-2021 was 100.5, 102.5 and 104.5, respectively, which was obviously unrealistic, so it was revised to 100. 5. Empirical result analysis In this paper, the time series data of 24 years from 1998 to 2021 are taken as samples and analyzed by Eviews 8 measurement software. Section 1 Descriptive statistical analysis and correlation test Table 4 The correlation coefficient between descriptive statistics and variables derived from Eviews software is merged. It can be seen from the table that the average age of first marriage is about 25.61 years old, and the difference between the maximum and minimum values in these 24 years is nearly 5 years old, and the overall median is 24.89 years old. In these 24 years, the domestic economy has developed rapidly, and people's concept of late marriage and late childbearing has become more and more popular. The minimum value of house price is 2053 yuan per square meter, and the maximum value is 10139 yuan per square meter, which is quite different. In the selected time, the house price has changed nearly five times. Aside from inflation, we can also see that the reform of the central and local fiscal tax- sharing system in 1992 has greatly stimulated housing prices, which is much higher than most other fields of material and asset production. Through covariance analysis, the correlation coefficients between the age of first marriage, the national average house price, the enrollment rate of senior high school, the population difference between men and women and the expenditure of 129 maternity insurance fund are 0.953, 0.760, -0.608 and 0.962, respectively, which shows that the variables are highly correlated, so we conduct regression analysis. Among them, the correlation coefficient between the age of first marriage and the national average house price and the expenditure of maternity insurance fund is above 0.9, which shows that there is a significant positive correlation. Table 4. Descriptive statistics and correlation coefficient of each variable Variable mean sd maximum minimum median 1 2 3 4 5 1. Age 25.609 1.517 29.660 24.210 24.890 1.000 2. Price 5147.417 2686.451 10139.000 2053.000 4856.500 0.953 1.000 3.Education 83.329 12.953 100.000 46.100 83.450 0.760 0.827 1.000 4. Gender 3587.625 315.252 4131.000 3070.000 3454.000 -0.608 -0.658 -0.390 1.000 5.Insurance 263.275 305.509 816.000 6.800 99.100 0.962 0.960 0.801 -0.666 1.000 Section 2 Stationary test In this paper, time series is selected, and most time series are unstable. In order to avoid pseudo-regression in OLS, unit root test is carried out before analysis. In this paper, ADF test is selected to judge whether each sequence is stable or not. ADF test results are shown in Table 5. From the test results, only the difference between male and female population and the expenditure of maternity insurance fund are stable in the original sequence, but the original sequence of the explained variable age at first marriage is not stable. Secondly, in the first-order difference sequence, the original time series is only stable at the significance level of 5%. In order to analyze the co-integration relationship of the same order difference sequence, the following co-integration test is carried out. Table 5. ADF test Variable Inspection form(C, T, K) ADF value Test value at 5% significance level P Test result age (C, 5) 7.926977 -2.998064 1.0000 unstable price (C, 5) 2.503033 -3.004861 0.9999 unstable education (C, 5) -1.053777 -3.020686 0.7126 unstable gender (C, T, 5) -4.387295 -3.622033 0.0106 stable insurance (, , 5) -5.428021 -1.961409 0.0000 stable Dage (C, T, 5) -1.693421 -3.632896 0.0197 stable Dprice (C, T, 5) -5.892420 -3.632896 0.0005 stable Deducation (, , 5) -2.394285 -1.959071 0.0195 stable Dgender (, , 5) -5.049398 -1.957204 0.0000 stable Dinsurance (, , 5) -3.209558 -1.062813 0.0032 stable Section 3 Cointegration test Simple linear regression was performed on the first marriage age, average house price, high school enrollment rate, population difference between men and women, and maternity insurance fund expenditure of the same order, and a residual sequence was generated. The residual sequence is tested by unit root, and the adjoint probability is 0.0264, which is less than 0.05. The original hypothesis is rejected and the residual sequence does not contain unit root. Stationary residual sequence means that there is a cointegration relationship between the explained variables and the explained variables. Figure 1. Co-integration test 130 Because the original sequence is non-stationary, it is necessary to carry out first-order difference on the original data based on the co-integration relationship of the same- order simplex sequence, establish an error correction model, carry out simple regression estimation, and derive Figure 2, and the result is as follows: 𝐷𝐴𝐺𝐸 0.0266703268244 0.000305665606719 βˆ— 𝐷𝑃𝑅𝐼𝐢𝐸 0.010478545041 βˆ— π·πΈπ·π‘ˆπΆπ΄π‘‡πΌπ‘‚π‘ 7.52373911277𝑒 05 βˆ— 𝐷𝐺𝐸𝑁𝐷𝐸𝑅 0.0023995428775 βˆ— π·πΌπ‘π‘†π‘ˆπ‘…π΄π‘πΆπΈ 0.468697165009 βˆ— 𝐸𝐢𝑀 1 Figure 2. OLS regression result after error correction Figure 3. Goodness of fit Figure 4. Regression results from 1999 to 2015 According to the OLS regression results, the adjusted R2 is 0.60 in goodness of fit test, so it can be considered that the 131 fitting effect is relatively good, and it can be seen from Figure 3 that the observed value fits well with the actual value; When Ξ±=0.01, F statistic = 7.25 > F Ξ± (4,22) = 4.31, which shows that the overall explanatory variables have a significant impact on the age of first marriage. That is, the equation is significantly effective at the level of 99%. From Figure 2, the coefficient of house price is 0.000306, and its P value is significant at the level of Ξ±=0.05, that is, 95%, indicating that every time the house price rises by 1 yuan/m2, the marriage age is delayed by 0.0003 years. This phenomenon can be explained by the fact that the rising house price will lead to the increase of people's marriage cost, which will lead to the decrease of people's willingness to get married, or that in order to pay the house price, they choose to accumulate wealth and get married, which will delay the first marriage age of our population. The equally significant variable is the expenditure of maternity insurance fund. The coefficient is 0.0024, which is significant at the level of 99%, indicating that the age of first marriage in China is delayed by 0.0024 years on average for every 100 million yuan increase in the expenditure of maternity insurance fund in China. There is a positive correlation between the expenditure of maternity fund and the age of first marriage, which is different from the social cognition. Through research, this paper finds that the maternity insurance fund has undergone tremendous changes during 2015 -2017, and the amount has risen dramatically, which may interfere with the research results. After research, the interpretation results are as follows. On the one hand, in March 2016, the Outline of the Thirteenth Five- Year Plan clearly stated that "maternity insurance should be combined with basic medical insurance" (Xie Tianchang, 2022) [14]. With the promotion of the pilot project of the merger of the two insurances, the coverage of maternity insurance has greatly increased, which has caused great fluctuations in the data of this period; On the other hand, in 2016, the liberalization of the "two-child policy" made a great contribution to the expenditure of the insurance fund, so as to stimulate the increase of the subsidy expenditure of the maternity fund, and the number of children increased rapidly in a short period of time, which objectively promoted the increase of expenditure. "Local governments have revised local family planning regulations, and in order to encourage young people to give birth, the family planning incentive leave formulated is merged with the original 98-day statutory maternity leave in the Provisions on Labor Protection of Female Workers, and all of them are paid by the maternity insurance fund." (Sun Jie, 2018 [15] ); In addition, after the introduction of the "two-child policy", the imbalance in the expenditure ratio of maternity insurance funds also contributed to this phenomenon; Many regions report that the maternity allowance used to pay maternity leave wages accounts for 60%-80% of the maternity insurance fund expenditure. Therefore, there may be some interference in this data, which needs special explanation. Based on this, this paper split this variable, taking the data of 2016 as the cut-off point, which was realized before the cut-off point, and the expenditure of maternity fund was negatively correlated with the age of first marriage, which was in line with social cognition; In 2016, due to a large number of non-quantitative situations such as policy changes and implementation, changes in social concepts and ideological trends, there is the possibility of cross-research with sociology and other disciplines, and a single econometric discipline is difficult to interpret. After research and discussion, this paper presents this issue separately for subsequent enlightening research. The enrollment rate of senior high school at the level of Ξ±=0.25 has a significant impact on the age of first marriage. Because the coefficient is negative, it shows that when the enrollment rate of high school increases by 1%, the age of the first marriage population in China is 0.01 years earlier on average. This paper holds that the improvement of education level has promoted the opening of ideas and the blending of diverse ideas, which is influenced by some advanced trends of thought, such as: flash marriage, naked marriage, honeymoon trip after marriage, etc. There may be a pattern that some youth groups choose early marriage. The coefficient of the population difference between men and women in marriage and childbearing is 0.0000752, which shows that when the population difference between men and women increases by 10,000 people, the age of the first marriage population in China is delayed by 0.0000752 years on average. This paper holds that this is based on the objective demographic and social factors, and the growing disparity between the sexes will lead to a sharp decline in gender resources. On the one hand, the uneven distribution of gender resources may induce gender conflicts and delay the age of first marriage. On the other hand, the disparity in the population difference between men and women will also lead to a variety of choices for the party with a numerical disadvantage, thus delaying the age of marriage; But on the whole, that is, the population of both men and women in China has a huge base, and this ratio will not have a great impact, that is, it will be significant at the level of 35% as revealed later, indicating that the difference between men and women is not so important to the age of first marriage. Section 4 Multiple collinearity test After that, the multicollinearity test is carried out to verify that there is a certain linear relationship between explanatory variables. Under normal circumstances, if the VIF value of explanatory variables is greater than 10, it means that there is serious multicollinearity and it needs to be corrected. Figure 5 is obtained after the test. Figure 5. Multiple collinearity test 132 As shown in Figure 4, the VIF value of each explanatory variable is less than 10, indicating that there is no multicollinearity. Section 5 Autocorrelation test Then the autocorrelation test is carried out. LM test was used in the study, and the result is shown in Figure 6. If the available p value is 0.1131, then the p value is > 0.05, indicating that there is no autocorrelation problem. Figure 6. Autocorrelation test 6. Conclusions and Suggestions With the development of economy and society, many small factors are becoming more and more important factors affecting the age of first marriage. Based on the relevant data of China Statistical Yearbook, using Eviews and Stata tools, this paper establishes an OLS estimation model, processes the data of several main factors affecting the age at first marriage, and analyzes the correlation influence of each factor on the average age at first marriage, and finally draws the following conclusions: First, there is a significant positive correlation between house prices and the age at first marriage, that is, the rise of house prices will lead to the increase of marriage costs, thus affecting the increase of the age at first marriage. Second, the enrollment rate of senior high school is negatively correlated with the age of first marriage, that is, the higher the social education level, the lower the national average age of first marriage. Thirdly, the population difference between men and women is positively correlated with the age of first marriage, but its significance is weak, so it can be concluded that the population difference between men and women is not a very important influencing factor on the age of first marriage. Based on the above empirical analysis, we put forward the following suggestions: First, we suggest that the state continue to promote relevant housing policies, curb the vicious growth of housing prices, adhere to the basic policy of "houses are used for living, not speculation", ensure the rigid demand of residents' housing, promote the steady development of the housing market, reduce the pressure on young people to buy houses, and thus reduce the age of first marriage. Second, continue to increase investment in education. Education is indispensable to improve the quality of the population. The emergence of new thoughts has greatly changed people's concept of marriage and contributed to the reduction of the final age of first marriage. Postponement of the age of first marriage is an inevitable trend of economic and social development. This paper makes a data analysis on the correlation influence, aiming at exploring the important factors that affect the change of the age of first marriage in combination with the current situation in China, so as to further provide suggestions for optimizing policies in related fields and reducing the age of first marriage as much as possible. Subsequently, with the development of the times, the correlation of factors will change, and the update of variables will be an important direction of research. I hope that the social problems discussed in this study can contribute to promoting development. References [1] Fang Li, Tian Chuanhao. Building a good nest can attract a good phoenix. Rural housing investment and marriage [J]. 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