Impact of Supply-Side Reform on the Development Trend of Chinese Real✅

Impact of Supply-Side Reform on the Development Trend of Chinese Real✅

Chapter One

Introduction

 

In 2015, with the decline on demographic dividend, the middle-income trap accumulation and the constant change in international economic structure, over recent years China has experienced a slower economic growth. The changes are evident in the studies of 2015 which portrayed a fall of 7% in economic growth. Therefore, economy is facing significant problems such as overcapacity, declines in corporate profits, high level of debts, leverage ratios and large real estate inventories. In this aspect, the Chinese president Xi Jinping in the year 2015, first announced the supply-side structural reform which evolved to a major component of the government economic reform framework. He emphasized on the five tasks to the reform namely; decreasing inventory, improving weak parts, reducing costs, deleveraging and solving overcapacity. The goals of these reforms were towards improving the weak China economic growth.

 

Also, in description of this issue illustrated in this paper, Supply-side is the opposite of supply-demand, which tends to have three forces, namely investment, export, and consumption. The troops are short-term in matters concerning economic growth rate. Whereas the supply-side has four significant factors, namely; capital, regulation, technology, and labor force, which tend to take extended time towards their improvement towards potential growth rate. It is, therefore, a long-term issue that requires institutional planning, which is in-depth and also adjustment, which is long-lasting. In housing, mostly the real estate in China contributes to the more significant portion of the country's economy.

As an essential component of China economy, the supply-side policy in the real estate industry is worth a desired attention.

The aspect suits on the policies focusing to reduce the distortions in the economy supply-side and also upgrading different sectors in the industry. They were therefore introduced towards dealing with a range of longer economic issues which were in part to create the policy response to the financial crisis. Thus, China had a set of export-led growth model in the period which led to the global financial crisis. The exports not only were contributing to growth but also much of the investment activities in China was being directed at building capacity on trade sectors mostly the manufacturing sector. In response to the weakened china demand and external economic condition sharp deterioration during the crisis, the Chinese government announced a financial package in the year 2008. Much of the spending was targeted on different kinds of infrastructure which caused fixed asset investment (FAI) growth. A lot of spending however, was accompanied by a significant expansion in both bank and non-bank lending.

 

The real estate in China has accumulated an excess stock sold to apartments. In various instances in China, the price changes could not have provided enough signals; however, policy interventions inhibited the allocation. For example, the desire towards avoiding excessive unemployment was an incentive, which keep unprofitable state-owned enterprises (SOEs) running. As the Government and other authorities sorted to keep expensive firms operating, the corporate debt remained on its increase, and the commercial banks were encouraged actively to expand more loans and roll over the obligations to assist. The cash flow need from the land sale use rights and local GDP growth target tend to encourage the provincial Government towards ensuring real estate developers continues to build.

 

As an essential component of the China economy, the supply-side policy in the real estate industry is worth the desired attention. In China, a large amount of real estate inventory is a resource waste manifestation in the real estate market, which is a great challenge in the reform. This inventory by the year 2017 amounted to 5.5 billion square meters of the total area, and the cycle inventory was 42.4 months after some time was reduced by 26 months with the end of the previous year.

 

The stock, however, is still higher than the 18-month standard, which is the upper limit of the inventory cycle in China's real estate market. Moreover, problems related to the supply-side policies in the housing market of many developing counties inclusion of the human resources, technology, capital, and land supply still exists. For example, as the prices of housings fell, the real estate market in many regions produced a significantly large number of redundant workers. As a result of the construction land supply imbalance, the supply-demand mismatches in the market exist in big cities. In various remote areas, housing enterprises tend to have significantly lower profit margins on technical input insufficient accounts. Moreover, under an economic intensified supply-side policy backdrop, a practical issue that needs to be addressed is determining how to identify the current supply scenario in the housing market, thus adjusting the outputs and inputs of different resources towards obtaining a higher return economically.

Furthermore, the real estate industry is a reformed product and has a promotion effect on national economic growth. Thus, the Chin economic rise applies to the real estate industry with support from the capital market that tends to be very risky. As shown above, in the year 2015 financial leadership group meeting introduced the supply-side reform, which was led by the president Xi. The industry, therefore, is scarce. Many decisions refer to excess capacity and reducing the inventory and also to promote sustainable development. It again reflects the China authority's determination towards regulating the market.

The real estate policy regulations over a few years ago have started with various housing demand and take short-term actions. Thus, this method cannot solve the problems of the industries involved in real estate housing in China. The supply-side policy now is not about inventory reduction, which stimulates the market subject vitality and carries out structural adjustments. The real estate regulations and supply-side combination structure are to change the situation so as the developers of real-estate could provide quality housing, which is also efficient. Thus, embarking from the economic situation as well as the Government's supply-side reform policy, the paper, therefore, assess its impacts on development trends in China's real estate.

Problem Statement

In China, real estate is one of the current emerging markets with vigorous reformation and rapid growth. The Chinese Government has completed the monopolizes the land quality control and the land market as well as the timing development. Towards improving the competition, which tends to arise on the market and process making for grant land rights more transparent, the China government in July year 2002 adopted a new competitive method. Since then, the ministry of lands and resources in China has therefore implemented regulations regarding different aspects such as the granting of government-owned land use rights through (1) auctions, (2) listings, or tender invitations. The new land policy was entirely adopted after August 31, 2003. The tender requests entail an announcement from the local Government of public land bidding, thereby natural persons, institutions, or legal persons are invited to bid as well as the land use rights are usually granted following the final result of the bidding process. The local government bidders thus announce it, and auction participates in the sense of auction, which is competitive at a designated place and time. The bidders have been quoting their prices publicly. However, the land use is therefore determined following the results of the quotations. Listing is defined as the process where the local Government places a specific notice at a place designated to the land exchange process.

 

The land grantor thus must disclose the conditions and terms for land right use right granting. After accepting the bidder's quotations, updates are made on the listing notice in a particular order. The rights on land use are therefore allowed based on the reference made at the final of the period involving the advice. The notice period includes at least ten days and is over. Different developers in China acquire rights on land usage through competitions that are fair in the land market, thus moving to the housing market in China. The land market threshold is, however, becoming lower, and the market is also growing too transparent and public. The effects of different factors on the prices of housing may have changed. This new system on the land use rights granting is therefore believed to have an impact on the dynamic relation which arises between the fundamental variables and housing prices. The previous study literature has not yet illustrated or, in other words, studied the land policy impact change on the dynamic behavior of the expenses regarding the housing.

 

China, therefore, has successfully experienced housing markets and private land development in such a short period, which provides it with various experimental insights to 2 in 2007, September 28. The PMC Ministry of land and resources (the MLR) promulgated the regulation on the state-Owned Construction land use rights via the Auctions, tender invitations, or listings. Decree No. 39 has expanded the mandatory land grant scope through different auctions, listings, or request of the tender to industrial land that includes; a property which is used for storage and warehousing, thus excluding the property which is used for mining.

Between the years 2002 to 2004, China's new land system and the old negotiation system were implemented both in the market. Consequently, the land policy impacted on the linkage between various fundamental factors a housing prices. Thus, China, despite increased innovation, is facing investments that are overheated regarding the real estate market. Real estate overinvestment brings, therefore, about supply tension in power, oil, and coal, pushing the basic product prices and other general level prices upwards. Thus, in conclusion to this problem statement, China facing these side effects, the state government has tried to adopt various macro-economic controls towards maintaining a moderate and steady economic development in the long run. Additionally, changes in policy may tend to have a substantial effect/impact on the housing price variation. This research thus, it assesses the effects of supply-side reform on the development trend of Chinese real estate.

 Chapter 2

Impact of Supply-Side Reform on the Development Trend of Chinese Real

Literature Review

With the growing real estate bubble perspectives in the Chinese economy. A lot has been speculated yet very little has been done to study the impact of supply-side reforms in the development of Chinese real estate. However, with the glorious development of the real estate sector, there is need to evaluate the efficiency of the supply-side reforms at least to understand its impact on the real estate. Several scholars have carried out studies on studying the impact and efficiency of supply-side reforms. This section will select the studies that are in line with our topic while assessing their similarity and differences in terms of study and results with our findings.

Study on Supply-side efficiency of Chinese Real Estate Market

Several studies have been carried out on the supply side efficiency of Chinese real estate market using two analytical methods i.e.; method of index analysis and the frontal analysis. The index analysis method can be used to examine market efficiency if the correct indexes of real estate as well as financial analysis are deployed. (Lee et al., 2012) examined the dynamic efficiency value of the real estate market by using the index futures. Also, (Kopczuk & Munroe, 2015) centered their study on the transfer taxes in the New York and New Jersey housing markets, and from their results, they made a conclusion that hefty transfer tax on luxury homes reduces the efficiency of the market. However, this method of index analysis to evaluate real estate efficiency as (Yeh, 1996) suggested that they incur some randomness in their process of index selection meaning the challenges of correlation as well as collinearity between the indexes proves impossible to solve which definitely will bring erroneous analysis results.

Farrell proposed the frontal analysis method in 1957 suggesting to measure efficiency with construction of the production-possibility frontier (PPF) (Farrell, 1957). The frontal analysis method is made up of two categories namely; the parametric and nonparametric methods (Granderson & Linvill, 1998). For instance, the stochastic frontier analysis (SFA) is extensively used in the academic papers while examining the real estate market efficiencies. The SFA method is preferred because it takes into consideration other random factors such a luck and weather in the output result making the efficiency output more credible and accurate. Though, using the SFA method while doing evaluation needs one to make assumptions such as the inefficient items should always adhere to the half-normal distribution which in most cases introduces a certain degree of an error in the efficiency evaluation in the actual analysis (Kumbhakar et al., 2012). Moreover, there is always a precondition of obtaining mathematical functions while using the SFA method while conducting efficiency evaluation. But when faced with the case of Chinese real estate market it is difficult to derive the mathematical function since this is a market with several inputs and outputs factors making it impossible to find a particular expression to get do the calculation (Leone & Ravishankar, 2017). While the method was successful in calculating real estate market in other countries, it has its own inefficiencies which makes the method not widely applicable in all regions. Hence, frontal analysis method with its categories cannot be used in our study since it is known to bring errors especially with the Chinese real estate market.

Charnes et al., (1978) made profound progress and great contribution in the field of market analysis following his introduction of the data development analysis (DEA) model in 1978. His method is the most commonly used as a nonparametric method in most current market analysis studies. When compared with the parametric method, the data development analysis does not require considerations of the particular form of production frontier or setting up a weight of each index as a precondition to the analysis. Besides, this method is not affected by any variable of factors. Thus, in the real estate market, this method is the most adopted and accepted for efficiency evaluations. For example, in one practical study, (Wang, 2005) designed a knowledge decision model using the data envelopment analysis in measuring the performance of government real estate investment. The system contained the 4 frequently used DEA models i.e. CCR, BCC, FDH and SBM, and it was realized that the method can help governments in calculating or evaluating various indexes related to real estate investment such as the input redundancy and returns to scale. However, the issue common with the DEA is the efficiency of many provinces hits their maximum levels concurrently. But (Wei at al. 2011) managed this issue by adopting the super-efficient DEA in evaluating the efficiency of Chinese real estate investment and they made a conclusion that there are disparities in efficiency of real estate investment across China ("Study on the Performance Evaluation of Real Estate Investment Trusts Based on Super-Efficiency DEA", 2012). Most of the investments are concentrated in the southeastern coastal regions as well as the northwestern regions thus the high efficiency values from these two regions as compared to other regions. This method can be used to calculate the efficiency in China real estate but it is not in line with out study of studying the impact of supply-side reforms in Chinese real estate where we will use the ordinary least square method.


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Date published: 22/09/2017
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