A Study on the Interaction among Financial Development, Industrial Adjustment and Urbanization

Yang YANG

School of Finance, Anhui University of Finance and Economics, Bengbu 233030, China

Abstract This paper attempts to study the interactive relationship among financial development, industrial structure adjustment and urbanization in China. Based on the data from 1978 to 2018, this paper establishes a VAR model for empirical analysis. The results show that after the impulse response analysis and variance decomposition of the model, industrial structure adjustment and urbanization have a positive impact on financial development in the long run. Financial development and industrial structure adjustment do not play a positive role in the process of urbanization, and there is still room for further development. It is suggested that the state should strengthen the financial support for urbanization so that the two can develop in coordination. At the same time, we should adhere to the simultaneous development of industrial structure adjustment and urbanization to ensure the simultaneous development of financial scale and efficiency.

Key words Financial development, Industrial structure adjustment, Urbanization development, VAR model, Interactive research

1 Introduction

Urbanization is an important embodiment of social construction modernization. From reform and opening up to now, China’s urbanization rate has developed rapidly, from the initial 17.92% to 59.58% in 2018. The rapid development of urbanization has not only fully liberated many rural labor force, but also promoted the rapid development of economy and the adjustment of industrial structure. China has changed from the development mode based on the primary industry to the economic progress led by the secondary and tertiary industry. At present, China is in a period of rapid development of urbanization, and a large amount of capital investment is needed for each additional urban population. Therefore, in the process of construction, the demand for investment funds is huge. As the main carrier of capital allocation, finance plays a huge role. Financial institutions need to give full play to their functions as financial intermediaries and allocate funds reasonably and efficiently for the construction of urbanization. Therefore, it is of profound significance to study the relationship among financial development, industrial structure adjustment and urbanization in China. In recent years, many scholars at home and abroad have done a lot of research on financial development, industrialization adjustment and urbanization. According to the existing literature, it can be divided into the following two aspects. (i) In the financial development and urbanization construction, Atack and others believe that the improvement of financial scale and efficiency can provide more financing models for the development of urbanization, so that the efficient allocation of funds is conducive to promoting the development of urbanization[1]. Shao Guangqing and Xie Yun (2013) chose to build a panel VEC model to empirically analyze the dynamic interaction between urbanization and financial development in different periods in China. The results show that financial development has a significant impact on urbanization in the short term, and there is an internal causal and interactive relationship between urbanization and financial development in the long run. Xie Jinlou selects the panel data of financial development and urbanization of 31 provinces in China, and establishes an econometric model to find that there is an inverse relationship between financial efficiency and urbanization construction, and financial scale and financial structure play a positive role in promoting urbanization[3]. Li Qingzheng and Liu Xuzuo establish a national VAR model and inter-provincial panel data for empirical analysis after studying the theory of financial support for the development of urbanization. They found that the scale of financial credit plays a significant role in promoting urbanization, while the role of urbanization in promoting financial development needs to be improved[4]. (ii) In the aspect of industrial structure adjustment and urbanization construction, Kolko makes an empirical analysis on the development of urbanization and industrial structure by constructing a dynamic panel model. He found that the development of urbanization is conducive to the development of the service industry, which can promote the rapid agglomeration of the tertiary industry, and optimize the regional industrial structure[5]. Wu Qiongetal. found that the rationalization and upgrading of industrial structure play a significant positive role in promoting the development of urbanization by constructing a new compound index system of urbanization and using the spatial lag econometric model. Huang Yajie studied the relationship between urbanization and industrial structure adjustment by selecting the data of 285 prefecture-level cities in China to establish an error correction model. The results show that the industrial structure is not only affected by the short-term fluctuation of urbanization, but also depends on the deviation trend of long-term equilibrium, and there are some differences in different regions of the eastern, central and western China[7]. Based on the perspective of supply-side structural reform, Zhou Min and others use the principal component and entropy method to measure the development level of urbanization and analyze the impact of urbanization on the upgrading and adjustment of industrial structure through two-stage generalized method of moments. The study found that the development of urbanization in China can significantly promote industrial transfer and industrial structure upgrading[8]. Based on the research of domestic and foreign scholars, it can be found that most of them only study the relationship between financial development and urbanization or the relationship between urbanization development and industrial structure adjustment, but there is little literature to unify the relations among the three. At the same time, when studying the relationship between each other, the selected time series indexes have great differences, and have not been effectively explained and adjusted according to the actual development of our country. Therefore, we choose reasonable index data according to the actual development situation of our country, establish VAR model, and make an empirical analysis on the interactive relationship among financial development, industrial structure adjustment and urbanization development through impulse response and variance decomposition.

2 Research methods

2.1 Data sources and index establishmentIn order to study the relationship among financial development, industrial structure adjustment and urbanization, this paper selects three representative indexes to study the relationship between variables. In the aspect of financial development, the index of financial development scale is selected, which can effectively reflect the role of financial intermediary function. It can better reflect the role of finance serving industry structure adjustment and supporting urbanization. In the aspect of industrial adjustment, in order to reflect the dynamic relationship of industrial structure, rather than the state of a point in time, according to the method of Wu Jinglian (2008), this paper uses the ratio of the added value of the tertiary industry to the added value of the secondary industry as an index to measure the adjustment of industrial structure[9]. In the aspect of urbanization development, in order to reflect the process of urbanization, this paper chooses the proportion of urban population as the measurement index of urbanization development. The data in this paper are all from the Wind database, and the data range is from 1978 to 2018, in which the GDP is the current price level of each year. As the lending volume of financial institutions is quarterly, it is replaced by the data of the last quarter of each year. In order to avoid the phenomenon of heteroscedasticity and the influence of time trend, it is necessary to perform logarithmic treatment on the established index data before modeling and analysis.

2.2 Model settingIn 1980, Sims introduced the vector autoregressive model (VAR) into the study of economics. After that, Granger and Engle supplemented the cointegration theory to this theory, so that the model is often used for the dynamic impact of time series systems and random errors on variable systems to explain the impact of various economic shocks on economic variables. Therefore, this paper studies the dynamic relationship among financial development, industrial structure adjustment and urbanization by establishing VAR model[10].

Yt=α0+α1Yt-1+α2Yt-2+…+αpYt-p+β1X1+…βqXt-q+Ut

whereYtis thek-dimensional endogenous variable vector;Xtis ther-dimensional exogenous variable;α0,α1,α2, …,αpandβ1,β2, …,βqare the parameter matrix to be estimated; the endogenous variable and the exogenous variable havep-order lag andq-order lag, respectively;Utis the random error term.

3 Results and analysis

3.1 Unit root testThrough the ADF unit root test, we can test the stationarity of the established time series index data, so as to avoid the occurrence of "pseudo regression" caused by the unstable data. Based on the established index data, this paper makes a stationarity test to determine the long-term equilibrium relationship among financial development, industrial structure adjustment and urbanization. From the test results, it can be seen that lnFDS, lnTSand lnURcannot pass the stationarity test at the level of significance. This shows that the established index data is unstable, and all the data need to be processed by first-order difference and judged and tested according to the SIC criterion. After the differential processing, all the index data pass the stationarity test, which shows that lnFDS, lnTSand lnURare integrated of order one sequences. At the same time, it also shows that there is a cointegration relationship between the index data, which needs to be further determined by cointegration test.

3.2 Cointegration testBefore the cointegration test, the optimal lag order of the model needs to be determined, and the cointegration test can only be carried out after the optimal lag order is known. A VAR model is established for all the index data to determine the lag order. The optimal lag order is judged according to the five information criteria. When the lag is 2, three of the five evaluation indexes are passed, indicating that the establishment of VAR (2) model is reasonable. In order to verify whether there is a long-term equilibrium relationship among the three index variables, Johansen cointegration test is needed. Because the model has two lags and the time series data index is integrated of order one, the lag needs to be reduced by 1 in the Johansen cointegration test. Through the test, it can be found that there is a cointegration among the variables. At the same time, it shows that there is a long-term equilibrium relationship among financial development, industrial structure adjustment and urbanization.

3.3 Establishment of VAR model and stationarity testAccording to the analysis, the VAR model with two lags is selected for parameter estimation, and the VAR (2) model is established by Eviews 9.0.

After the establishment of VAR, the stationarity of the model needs to be tested, and the test results are reflected by the AR root chart. If all the reciprocals of root modules are less than 1 and fall within the unit, it shows that the established VAR model is stable. According to the stationarity test of the model, all the root modules fall into the unit circle. This shows that the established model is stable and can be further analyzed.

3.4 Variance decompositionVariance decomposition is a further analysis of the contribution of each endogenous variable to the predicted variance. The variance decomposition model can well measure the degree of information presentation and clarify the contribution degree of each variable in the system[12]. After the variance decomposition of each index variable, we can well analyze the contribution degree of the three variables. The variance decomposition of the model shows that when decomposing lnTS, the contribution rate of lnFDSand lnURto lnTStends to be stable after the fifth period. The average contribution of lnFDSand lnURto lnTSis 5.08% and 16.32%. Financial scale and urbanization development promote the adjustment of industrial structure to a certain extent, but the contribution rate is relatively low. When decomposing the variance of lnFDS, the average variance contribution rates of lnTSand lnURto lnFDSare 11.45% and 24.72%, respectively. The variance contribution rate of lnTSto lnFDStends to be stable in the fourth period, but has a downward trend in recent years. This shows that the adjustment of industrial structure has led to the rapid development of the tertiary industry. In response to the call to serve the real economy, the investment in the financial industry has decreased, resulting in a slowdown in the scale of financial development. The contribution rate of lnURto lnFDStends to be stable in the fourth stage. Compared with the contribution rate of industrial structure, the contribution rate of urbanization to the scale of financial development is high. This shows that there is a great demand for financial institutions and capital allocation for the urbanization in the process of development. In the variance decomposition of lnUR, the contribution rate of lnFDSand lnTSto lnURincreases with time. The average contribution rate of lnFDSand lnTSto lnURis 15.41% and 1.56%, respectively, indicating that with the continuous development of the urbanization process, the effect of financial development scale and industrial structure adjustment on it is more obvious[13].

4 Conclusions and recommendations

In order to study the interactive relationship among financial development, industrial structure adjustment and urbanization development, this paper selects three time series index data from 2002 to 2018. Through data stationarity test, cointegration test and variance decomposition, this paper makes an empirical study on the relationship among China’s financial development, industrial structure adjustment and urbanization development, and draws the following conclusions. In the stationarity test, it can be found that lnFDS, lnTSand lnURare not stationary time series data. After the first-order differential processing, they are found to be integrated of order one time series data. Through the cointegration test, it is known that there is a cointegration relationship among lnFDS, lnTSand lnUR, and the VAR model can be established. From the VAR (2) parameter estimation formula, there is a long-term equilibrium relationship among financial development, industrial structure adjustment and urbanization development, and financial development has a positive impact on industrial structure adjustment and urbanization development. Based on the above conclusions, this paper chooses to put forward the following recommendations. (i) Increasing the financial support for urbanization so that the two can develop in coordination. It is necessary to give full play to the function of financial intermediary through financial institutions and promote the adjustment of industrial structure and the construction of urbanization. At the same time, we also need to speed up the reform of the financial system and improve the financial service system, and formulate a credit financing model to serve the development of urbanization. In order to expand the financing channels for the construction of urbanization, it is necessary to carry out the reform of financing securitization with the help of financial institutions, so as to make financial development better serve the development of industry and the construction of urbanization. (ii) Synchronously developing the adjustment of industrial structure and the construction of urbanization. At present, there is still room for further adjustment of industrial structure in rural areas of our country. In the long run, the development of urbanization has a positive effect on the adjustment of industrial structure. Increasing the adjustment of the industrial structure in rural areas not only adjusts the industrial structure but also promotes the process of urbanization in rural areas. (iii) Strengthening the synchronous development of financial scale and efficiency. The financial development is the main driving force of industrial structure adjustment and urbanization. If the financial development only pays attention to the expansion of scale and does not pay attention to the improvement of efficiency, then it will only cause the loss of the time and capital value. The allocation of funds should be operated efficiently to better serve the development of various industries in order to better promote the adjustment of industrial structure and the development of urbanization.