Sponsor(s):Institute of Economics, Chinese Academy of Social Sciences
ISSN:0577-9154
CN:11-1081/F
12 issues per year
Current Issue: Issue 10, 2020
Total Downloads:1811
Journal official website:http://www.erj.cn/en/default.aspx
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Economic Research Journal is supervised by Chinese Academy of Social Sciences, and sponsored by Institute of Economics, Chinese Academy of Social Sciences. It aims to conduct researches on the new situation and new problems in China’s reform and opening up, economic development and transformation. Its scope covers all fields of China economics, including economic theory, finance, taxation, enterprise, new rural construction, marketing and accounting, etc. The journal, included in CSSCI, possesses a very high academic position in both domestic and oversea economic and management domain with which you can have a overall understanding about China’s comprehensive economics.
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Editor-in-Chief
Pei Changhong
Deputy Editor-in-Chief
Zhang Ping, Zheng Hongliang, Wang Cheng
China’s regional gap and supply-side structural reform: endogenous growth in a transition period
DENG Zhongqi;GAO Tingfan;ZHU Feng
Economic Research Journal,2020,Vol 55,No. 10
Since 2013, there has been a new trend in China’s economic geography: the gap between the northern and southern regions is gradually widening. The GDP, GDP per capita, growth rate, and production efficiency are all lower in the northern region than in the southern region, and there has been no obvious trend of the gap narrowing. This study’s statistical analyses identified two stylized facts about the north-south gap: the “2013 phenomenon,” when in the absence of major economic events, the gaps in the economic aggregates and growth rates between the north and the south widened suddenly; and the “2016 phenomenon,” when the gap between the north’s and the south’s economic aggregates widened further, the gap in total factor productivity (TFP) began to narrow. Few studies have used theoretical or quantitative analyses to clearly explain these differences between the north and the south or their underlying causes. This study fills this gap. Reviewing the history of economic growth since the founding of the People’s Republic of China, this study found that the underlying cause of the current gap between the north and the south is the transformation of the economic growth pattern. Using an iterative method based on the slack-based measure-directional distance function (SBM-DDF), we found that from 1998 to 2018, capital, labor, energy, and TFP were responsible for 74.7%, 2.1%, 14.8%, and 8.3% of economic growth, respectively. It is indisputable that China’s growth miracle has come from this capital-driven economic growth pattern. In the 21st century, the transformation of the south has been relatively successful, whereas the transformation of the north has been relatively unsuccessful. Under the shock of the 2008 global financial crisis and supply-side structural reform pressure, the north has been compelled to change its growth pattern, and has thus suffered more than the south. On the basis of this insight, this study empirically determined that the widening gap in 2013 was the result of the governmental economic stimulus plans that postponed the problems of 2008 to 2013. In the absence of economic transformation and upgrading in the northern region, the north-south gap would have appeared eventually; the global financial crisis was simply an accelerant, and the economic stimulus plans created a temporary isolation zone. Transformation is the only way forward for China’s economic development. Nonetheless, it has been unsuccessful since the 1980s. After the economic stimulus of 2008, the old model of extensive growth was re-adopted, especially in the northern region. Endogenous growth in China then picked up until the launch of the supply-side structural reform at the end of 2015. This conclusion is verified by our empirical evidence. As the northern region had reached the point where it had to change, the supply-side structural reform had a stronger effect on the endogenous growth of the northern region and thus narrowed the north-south gaps in TFP and the endogenous growth rate. However, an investigation of the spatial distribution of micro innovative enterprises revealed that the significant effect of the reform in the north is mainly due to the fact that “more problems are easier to get rid of,” and it is not easy to maintain a long-term endogenous growth in the north. Given the above findings, this study made the following suggestions. First, the government needs to continue its supply-side structural reforms. Second, the government must further promote intensive urbanization and industrial upgrading. In these areas, the southern region has taken the lead and obtained first-mover advantage. Third, the government must pay more attention to the agglomeration of enterprises, especially innovative enterprises. The northern region cannot rely entirely on market-led resource allocation, which, under the current economic geography pattern, would lead to the Matthew effect between the north and the south and the siphon effect of factors. Local governments should improve the business environment and enhance services.
Does access to credit availability encourage corporate innovation: evidence from the geographic network of banks in China
CAI Qingfeng;CHEN Yihui;LIN Kun
Economic Research Journal,2020,Vol 55,No. 10
How does credit availability from banks affect firms’ innovative activities? The answer to this question is crucial to unraveling how financial development can effectively promote a country’s economic growth. The empirical evidence suggests that financial development has a positive effect on firm innovation (Benfratello et al., 2008; Cai and Dong, 2016). However, financial development has been measured in terms of the overall amount of credit (Guiso et al., 2004; Ji, 2013) or the amount of credit at the regional level (Xie and Fang, 2011; Tang and Wu, 2015). Few studies have focused on the geographic network of bank branches, which gives us rich variations at the firm level. Based on the premise that distance erodes banks’ ability to acquire borrower-specific information, Hauswald and Marquez (2006) formally analyzed lending relationships under locationally differentiated information. They proposed that banks derive cost advantages from being geographically closer to the borrowing firms, as it is easier for banks to maintain loan relationships with firms that are closer to them. This means that the geographical network of bank branches that determines the availability of firms’ credit resources also affects innovation activities and the growth of the economy. China’s financial system is characterized by a typical bank-dominant system. At the end of 2018, China’s banking assets (CNY 268 trillion) accounted for nearly 90% of China’s total financial assets (CNY 300 trillion). Outside of financial centers such as Beijing, Shanghai, and Shenzhen, China’s financial geographic structure is largely determined by the layout of bank branches. Therefore, the financial resources that a firm can obtain mainly depend on the number of bank branches nearby. In addition, China and other countries such as the United States, European countries, and Japan have adopted easy monetary policies to stimulate economic growth since the 2008 financial crisis. However, the easy monetary policy, in the form of large amounts of bank credit, has not prompted firms to accelerate innovation or increase R&D investment. Instead, a large number of firms have leveraged production capacity using “cheap” bank credit resources. In February 2019, China began a financial reform designed to better serve the real economy’s structural transformation and upgrading under the guidance of a government proposal to “deepen the structural reform of the financial supply and better serve the real economy.” Against this background, this paper studied how the availability of credit, measured in the geographical organization of the bank system, affected firms’ innovation activities in the real economy. Using the number of bank branches around the listed company as a proxy variable for access to bank credit, we investigated the link between access to bank credit resources and firm innovation using a panel fixed-effect model. Our results showed that firms with more bank branches nearby have less R&D investment, particularly state-owned firms and large firms. The results are robust to the addition of more control variables and comparison to a placebo test. Further, the negative relationship between access to bank credit and firm innovation is mainly driven by large state-owned banks, whereas joint stock banks and local small and medium-sized banks have positive effects on firm innovation. In addition, we confirmed that proactive leverage is the mechanism through which access to bank credit affects firm innovation. Finally, firms with more credit availability tend to overinvest and divert more credit to investment in the real estate sector. Our findings explained why firms that have better credit availability reduce R&D investment. China’s financial reform has been steadily pushing forward, given its importance for economic development. This paper focuses on China’s geographic network of bank branches at the micro level, and is the first study to detect its negative effect on firm innovation, which is important for economic development. It also shows various mechanisms through which access to credit affects firm innovation, such as proactive leverage, overinvestment, and investment in the real estate industry. Whereas previous studies measure the availability of financial resources overall or at the regional level, the micro level measure, in terms of bank-firm distance and financial geographic structure, allows us to better investigate the mechanisms. We thus contributed to the literature on finance and firm innovation. In addition, our results have implications for financial reforms in developing countries worldwide that are characterized by bank-led financial systems.
Guaranteed bubbles: a dynamic general equilibrium analysis of financial risks and rigid redemption
DONG Feng;XU Zhiwei
Economic Research Journal,2020,Vol 55,No. 10
As financial system risks continue to grow, concerns about asset bubbles are increasing. The consensus is that, explicitly or implicitly, the guaranteed bailout (i.e., rigid redemption) of high-risk financial assets encourages investors to take greater risks, leading to excessive speculation and asset price bubbles, which threaten the stability of the macro system. However, academia has not fully explored how guaranteed bailouts affect asset bubbles and how a government can implement a prudential policy of guaranteed bailout. To this end, this paper introduced financial system risk and rigid redemption into an infinite-period asset bubble dynamic general equilibrium model and attempted to answer the following questions. How does rigid redemption of high-risk financial assets generate the so-called “guaranteed bubbles”? Given the existence of asset bubbles, how does the guaranteed bailout affect asset prices and the overall macro economy? At the macro level, is there an optimal rigid redemption policy? Our analysis framework was based on the infinite-period rational bubble model of Wang and Wen (2012). The model assumed that firms face heterogeneous shocks to investment efficiency. Under financing constraints, firms with higher investment efficiency cannot obtain desirable liquidity from the credit market. Therefore, resource misallocation exists. The incompleteness of this financial market endogenously creates the necessary conditions for the existence of asset bubbles that can provide liquidity. In turn, asset bubbles can improve liquidity to a certain extent and promote corporate investment. Asset bubbles may burst. We assumed that once a bubble bursts, the government will bail out a certain proportion of the bubbly assets. We showed that this policy makes the entire economy more prone to bubbles, so we called it a “guaranteed bubble” policy. This policy causes more liquid companies to hold bubbles even if the asset itself is highly risky. At the same time, greater demand for asset bubbles directly pushes up asset prices, causing an increase in the size of asset bubbles in equilibrium. We further demonstrated that when financial risks increase, guaranteed bailout obviously boosts asset prices and bubble size. When financial risks increase, the guaranteed subsidy for a bubble burst is essentially a bailout policy that encourages the expansion of asset bubbles while also increasing market liquidity. It then plays a positive role in investment and production. However, due to the inherent risks of bubbly assets, the guaranteed bailout will cause a crowding-out effect on the real economy. Our analysis showed that due to the trade-offs faced by guaranteed bailout policies, there is an optimal guaranteed bailout level, and the optimal value decreases as financial risks increase. In the case in which high financial risks and asset bubbles coexist, the government’s rescue policy for the capital market must be implemented cautiously. In sum, when the risk to the financial system is increasing, macro policies that deal with asset bubbles need to be resolved urgently. Using a dynamic general equilibrium model with rational asset bubbles, this paper investigated the causes and macroeconomic consequence of asset bubbles in the context of increased financial risk. We theoretically proved that asset bubbles are conducive to alleviating the liquidity shortage caused by financing constraints, thus improving the resource mismatch caused by financial frictions to some extent. However, asset bubbles also increase financial system risks, which pose a threat to the macro economy. After introducing the guaranteed bailout into the benchmark model, we found that the implicit bailout of high-risk financial assets leads to excessive speculation by investors with sufficient liquidity and thus cause guaranteed bubbles. The demand and price of bubbly assets are therefore positively related to the generosity of the implicit bailout. Our further analysis showed that guaranteed bubbles generate a crowding effect on the real economy while improving the liquidity shortage. Therefore, a government’s bailout policy creates competing effects, and thus, optimal policy decreases with the risk of the financial system. Our theoretical analysis revealed that given the coexistence of high financial risks and asset bubbles, the optimal bailout policy for financial markets must be selected with caution.
Health status of the middle-aged and elderly and household asset allocation: portfolio choice with liquid and illiquid assets
ZHOU Huijun;SHEN Ji;GONG Liutang
Economic Research Journal,2020,Vol 55,No. 10
Health risk is one of the most important background risks and may exert a significantly influence on an individual’s wealth accumulation and well-being. The negative shock of disease brings about higher demand for liquidity and changes people’s attitude toward asset liquidity and their investment psychology. How does health status affect Chinese households’ portfolio choice regarding liquid and illiquid risky assets? What are the primary determinants of the observed patterns? This paper attempts to answer these questions within a unified framework. We built a continuous-time optimal consumption and portfolio choice model based on Merton’s seminal work in which both liquid and illiquid risky assets are available for trading and investors are exposed to health risks. Trading a liquid asset incurred no transaction costs, so its purchase and sell prices were exactly the same. However, there was a bid-ask spread for the illiquid asset, where the spread was proportional to the purchase price. Our analysis showed that a household should focus not only on the absolute value of its liquid and illiquid wealth, but also on their relative magnitude. When the wealth of the illiquid asset account was too high relative to the wealth of the liquid asset account, the household should increase its holdings in liquid assets and reduce its holdings in illiquid assets. Conversely, when illiquid asset holdings were too low relative to liquid asset holdings, the household should reduce liquid assets and increase illiquid assets. When the ratio was in a medium range, the household should not adjust its illiquid assets holdings. An investor is healthy at first but over time will become irreversibly unhealthy. An unhealthy investor receives less labor income, but his healthcare expenditure increases, which should be drawn from liquid asset account. Worsening health also shortens an investor’s planning horizon. These two forces led to the following two testable implications: on the one hand, a change in health status exerts a large impact on the household’s holdings of illiquid assets; on the other hand, its impact on the household’s holdings of liquid assets is ambiguous. We used survey data from the China Health and Retirement Longitudinal Study (CHARLS) 2011–2015 to test the model’s implications. Our empirical evidence confirmed that households with bad health status tend to choose significantly lower holdings in housing investment than those with good health status. Our exploration revealed that this effect is mediated by a precautionary saving motive and the expectation of a shortened life span consistent with the model. When the explanatory variable was replaced by the holding of liquid risky assets, the result still held but exhibited much weaker significance and robustness. Finally, we conducted some robustness checks. We used the variable whether an individual has suffered from an accident or other unexpected, severe injury as an instrumental variable to solve the endogeneity problem. We also found that the policy intervention of home buying restrictions in a subset of cities does not affect our main results. The paper provides several policy implications. According to modern finance theory, in a complete market with sufficient financial tools, health risk as a typical idiosyncratic (negative) shock could be diversified to a large degree such that its impact on an individual’s consumption and asset allocation will be limited. However, our findings are far from this ideal outcome. The fundamental approach to eradicate poverty caused by illness is to improve the public health system and promote investment in social health. Further development of the financial market also matters; for example, the design of well-priced insurance products with stable yields that meet households’ needs merits further research. In addition, financial intermediaries should collaborate with medical institutions to provide loans to suffering households using housing as collateral. Finally, the development of the digital economy and “Internet+technology” will facilitate the organization of social resources to help families in need via crowd-funding platforms.
How the rise of robots has affected China’s labor market: evidence from China’s listed manufacturing firms
WANG Yongqin;DONG Wen
Economic Research Journal,2020,Vol 55,No. 10
The rise of AI and robots has been changing the economy and society. While these technologies have boosted productivity and economic growth, they have increasingly replaced workers in every industry and have posed unprecedented challenges to labor markets. Then, as the world’s top user of robots, China has an important question to answer: how have robots affected China’s labor markets? Currently, the existing empirical studies primarily focus on developed countries, and there is scant evidence from developing countries. Although there are some theoretical discussions on the rise of AI and robots in China and its economic consequences, a systematic and in-depth empirical research is still yet to come. This paper is to fill this void. To our knowledge, this paper is the first to study the effect of robots on China’s labor market using micro-data and among the first to study the effects of robots worldwide. The paper used data on China’s listed manufacturing firms and robot usage data from the International Federation of Robotics (IFR). It employed the Bartik IV to establish causality. The paper further explores potential mechanisms. To measure the exposure of firms to robots, we constructed a variable, industrial robot penetration. It is a Bartik-like instrumental variable, defined as the interaction between the industry-level density of robots and the weight of the firm in the industry. The weight was defined as the ratio of the employment share of production workers of the firm to the median of the employment shares of all of the manufacturing firms in the baseline period. To address endogeneity problems, we instrumented China’s industrial robot penetration using an analogous measure constructed from the industry-level density of robots in the United States. This allowed us to causally estimate the impact of exogenous improvements in technology on China’s labor markets. A priori, there are three main effects of robots on labor markets, which have different directional implications for labor markets: the substitution effect, the productivity effect, and the job creation effect. The ultimate effects are an empirical question. The results showed that there was a substitution effect between robot penetration and labor demand: a 1% increase in penetration reduced labor demand by 0.18%. The results also showed that there was substantial heterogeneity among workers with different skills, resulting in a job polarization effect. The adoption of robots mostly reduced the demand for middle-skill workers (i.e., those with bachelor’s and associate’s degrees): the elasticity of substitution was −0.27 and −0.44, respectively, for these two groups. There was a crowding-in effect for low-skill (high school degree or lower education) workers, but no significant effect for high-skill (graduate) workers. In addition, robots have a little effect on wages. One possible explanation for this result was wage rigidity. In terms of channels, the substitution effect was more salient in more concentrated industries (market power channel), industries with more credit constraints (credit constraint channel), and private firms vis-à-vis state-owned firms (resource constraint channel). The paper further explored the network effect of robots on labor markets. The results showed that the adoption of robots will have an effect on labor demand of upstream and downstream firms through input-output linkages. These results have important implications for China’s labor market and policy making. In particular, relevant policies should be considered with competition policies, financial policies, and social insurance policies together. To be more specific, firstly, the findings suggested that there was a substitution effect between robot penetration and labor demand, especially for middle-skill workers. In this regard, improving the social security system, especially increasing the coverage of unemployment insurance and strengthening social security for informal sector workers, may help mitigate the negative shocks caused by robots while exploiting the overall productivity gains. Secondly, because AI and robots also create new jobs, job training matters for both efficient and inclusive economic growth in the era of AI. Finally, implementing fair competition policies and easing financial constraints on firms can also help China create more employment to promote high-quality development in the brave new world of AI.
Branch geographical distribution, bank competition and firm leverage
LI Zhisheng;JIN Ling;KONG Dongmin
Economic Research Journal,2020,Vol 55,No. 10
As China’s economy is transitioning from high-speed growth to high-quality growth, it is very important to improve credit resource allocation efficiency at the macro level and fund utilization efficiency at the micro level. Due to soft budget constraints and government concerns about economic instability, a large quantity of credit resources flow into zombie firms and weak firms to ensure stable employment and local tax revenue. The privileging of zombie firms distorts credit allocation and crowds out credit to healthier and more productive firms. This structural problem of credit resource allocation seriously hinders the process of China’s high-quality development. In contrast to other developed and emerging economies, China’s financial system is dominated by a large but undeveloped banking sector. According to statistics from the People’s Bank of China, bank loans accounted for 64.94% of social financing in 2019. Since the 1980s, China’s banking system has been under reform as part of the economic opening up policies. In the past, the big five state-owned commercial banks dominated China’s banking market, with more than 70% of the total lending business, and the establishment of branches by joint equity banks and local commercial banks was strictly regulated. In the last two decades, China’s banking system has undergone significant changes, allowing joint equity banks and local commercial banks to operate more like their state-owned counterparts. In 2006 and 2009, China’s Banking Regulatory Commission relaxed the entry restrictions on opening new branches for joint equity banks and local commercial banks. The number of branches and the market share of joint equity banks and local commercial banks have been increasing significantly following this deregulation, which has enhanced bank competition and banks’ ability to support economic development. In this paper, we investigated how changes in banks’ geographical distribution and increased bank competition affect firms’ leverage decisions. We use the number of bank branches within a certain radius around firms to measure the level of bank competition. Using 2000–2012 Chinese Industry Census data, we found that a higher number of bank branches around firms had a significantly positive effect on firms’ leverage for the whole sample and the sub-sample of non-state firms and high productive firms. However, we also noticed that the regression coefficient of the number of bank branches was statistically significant and negative for state firms and zombie firms. This indicated increased bank competition can stimulate the increase of “good leverage,” which effectively improved the efficiency of bank credit resource allocation. Our findings were robust to a series of alternative empirical designs such as controlling reverse causality, utilizing bank deregulation as an exogenous shock, and two-stage least-square regressions to control potential endogeneity. Further study indicated that a higher number of branches affected firms’ leverage mainly by alleviating financial constraints via the market mechanism but impeded relationship lending. We also investigate whether bank competition improved firms’ capital structure, and we found that underleveraged firms benefited more and that firms in an area with more bank branches adjusted their capital structure more rapidly. This study enriched the literature on banks’ geographical distribution, bank competition, and firms’ leverage decisions and provided empirical evidence for policy making to reform and develop the banking industry. We provided detailed analysis and established causal links between banks’ geographical distribution, bank competition, and firms’ leverage decisions. In recent years, the Chinese government has made great efforts to improve the accessibility and affordability of financial services. Our findings provided empirical support for China’s marketization reform of the banking sector and the development of inclusive finance. Our study has important policy implications. In the process of promoting structure deleveraging and improving the efficiency of financial resource allocation, the government should attach great importance to the construction and improvement of the bank competition environment and try to strengthen the role of the market mechanism.
Cumulative tariff cost rate and structure in the global value chain: a theoretical and empirical study
NI Hongfu
Economic Research Journal,2020,Vol 55,No. 10
In the current interconnected global value chain, enterprises exchange intermediate goods across borders many times. The value of their products is created by many factors in different regions. Obviously, products and services face various trade costs in the transaction process, and the tariff cost has always been a core issue. The recent rise of antiglobalization, trade protectionism, and the increasing trade frictions between China and the United States, have had huge impacts on global trade and economies. The sudden outbreak of the coronavirus pandemic has also had negative effects. What is the amplification effect of China’s tariff cost and its trends? How much does China contribute to global tariff costs? Is it because of China’s higher import tariffs or because of the structural changes in the global production network? It is of great practical significance to measure the cost of tariffs in the global value chain and to investigate the amplification effect and mechanism of tariffs in the value chain. In the global production network system, trade costs are generally transmitted and absorbed in the production process and are embodied in the product price. Is there a cost chain parallel to the value chain, and does production fragmentation hinder or promote trade? Although the nominal tariff rate is relatively low, the tariff protection effect should not be ignored, given the amplification effect across the global production network system. Policy concerns and the development of theories have prompted research on the trade costs in global value chains. Although these studies define the cumulative tariff cost rate from different economic perspectives, their final calculation formulas are similar, which can be attributed to their use of the input-output price model. However, these methods are relatively scattered. This paper constructed a more unified measurement framework from the perspective of the Leontief inverse matrix. Under the unified calculation framework, calculation formulas for the cumulative tariff cost rates in other studies were obtained by taking different special cases. In the classical input-output analysis methods, the Ghosh’s inverse matrix and Leontief inverse matrix are similar, so it is natural to consider whether using the Ghosh’s inverse matrix can provide a better understanding of the cumulative tariff cost rate. At the same time, referring to the four-term decomposition method of Leontief inverse matrix in Muradov (2016), this paper provided two new decomposition methods: (1) the cumulative tariff cost rate of the domestic value chain and the cumulative tariff cost rate of the international value chain; and (2) the direct tariff cost rate and multi-stage cumulative tariff cost rate. Empirical research using World Input-Output Table (WIOD) and tariff data revealed the following. (1) On the whole, China’s cumulative tariff cost rate, direct tariff cost rate, and multi-stage tariff cost rate show downward trends, and the degree of the decline is greater than that of the global cumulative tariff cost rate. Since China’s accession to the WTO, it has strictly fulfilled its WTO commitments and substantially reduced the tariff rates on imported intermediate products. (2) The amplification effect of China’s tariff cost has shown a significant upward trend, and the tariff cost for all countries (regions) worldwide has an amplification effect (more than 1.5). (3) China’s contribution to the global cumulative tariff cost rate is the largest. The complexity of the global production network structure is the decisive factor in China’s contribution to the global cumulative tariff cost rate. (4) There is a positive relationship between the cumulative tariff cost rate and its downstream degree in the global value chain. (5) The scenario simulation results for the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) show that only if China and the United States join the CPTPP at the same time will the cumulative tariff cost rate of CPTPP member countries and other countries decrease significantly. It is therefore proposed that China, India, and other developing countries further reduce their import tariffs and that China continue to advocate and promote trade and investment liberalization and facilitation, and oppose any form of protectionism.
Market signaling of educational background: evidence from a field experiment
LI Bin;BAI Yan
Economic Research Journal,2020,Vol 55,No. 10
Since 1999, the Chinese government has implemented a policy of large-scale expansion in the field of higher education. The number of undergraduate enrollments in China has increased from 653,100 per year in 1998 to 4,108,100 per year in 2017. Over the same period, the number of graduate students enrolled in China rose from 57,500 to 722,200. It usually takes two years to obtain a Master’s degree. However, in China, Master’s degree candidates usually find a job in the second year on campus. Since May 1998, the Chinese government has launched the 985 Project, the 211 Project, and other financial support projects to promote the development of world-leading universities. The 985 Project selected 39 universities and the 211 Project selected 112 universities (the 39 universities in the 985 Project were included in the 211 Project). These universities account for 1.3% and 3.8% of all Chinese universities (almost all of which are public universities), respectively. The 211 Project universities receive far more financial support from the government than other universities. This financial support has led to a rapid improvement in the average level of these universities and widened the gap between them and the other universities. Graduates of the 211 Project universities have special status, and they receive exceptional treatment. Because the college entrance examination is the most common way for Chinese people to advance professionally, this status may accompany them for life. Therefore, even if undergraduate graduates of non-211 Project universities are admitted to 211 Project universities to study for a Master’s degree, they may still be discriminated against by employers in job hunting after graduation. Empirical studies have provided little robust evidence of the existence of such first-degree (i.e. Bachelor’s degree) discrimination and have not begun to explore the reasons. Following the method used by Bertrand and Mullainathan (2004), we designed a field experiment for resume delivery. In the experiment, we sent a large number of resumes of Master’s graduates who graduated from the 211 Project universities to recruiters. By comparing the interview notices received by those with non-211 undergraduate degrees and those with 211 undergraduate degrees, we looked for evidence of first-degree discrimination. The results of the experiment showed that for initial employment, the response rate for CVs from graduates with first degrees from non-211 Project universities was 41% lower than that for graduates with first degrees from 211 Project universities. Better internship experiences, school performances, and qualification certificates increased response rate significantly and decreased first-degree discrimination. No significant first-degree discrimination was found in social recruitment. Therefore, there may be statistical discrimination based on the first degree in the hiring process. This paper has made two core contributions. First, it is the first paper to use field experiments to study first-degree discrimination. By controlling personal characteristics such as job applicants’ abilities, we obtained robust evidence of the existence of first-degree discrimination. Second, this paper found through field experiments that first-degree discrimination involves statistical discrimination motives, that is, the first degree is to a certain extent a quality signal under asymmetric information, which employers use in estimating the expected productivity levels of different job-hunting groups. This paper provides sufficient evidence to prove the existence of first-degree discrimination in campus recruitment. Based on this discovery, we believed that the government and the news media should no longer promote projects like the 211 Project, as they lead to identity discrimination in job markets and ultimately decrease the economic efficiency of labor markets.
Data capital and economic growth path
XU Xiang;ZHAO Mofei
Economic Research Journal,2020,Vol 55,No. 10
Economic growth in the digital age differs from the past in two ways: new factors of production have been introduced and new patterns of production and economic growth have been created. A new economic growth model that takes these changes into account can help us better understand the impact of the new elements of the digital age on economic development. In this paper, we defined data capital and explained how it affected the production process. Data capital is defined as data and digitized information that are carried by modern information networks and databases, use information and communication technologies, and are processed and transformed into production factors. Data capital combined with ICT capital becomes a compound input into production, and it increases social production efficiency by improving firms’ allocation of production factors. The latter effect features two innovations: it gradually increases firms’ production efficiency through technological innovations, and it increases the industry’s ability to process new data, which indicates the efficiency of data capital formation. Given these two effects, it is important to understand the relationship among data capital growth, the digitization of production factors, and economic growth. In China’s high-quality growth stage, data capital will play a bigger role than traditional capital and ICT capital. We built an endogenous growth model to analyze the direct impact and spillover effect of data capital on economic growth. We first constructed the microeconomic structure of how data capital, as a direct input of production, affects firm production by improving firms’ business decisions. By smoothing the random innovation process, we eliminated the firm stochastic heterogeneity and built a micro foundation for the following macroeconomic analysis. The micro structure suggested that the smoothed innovation process was comparable to the “learning by doing” process in both technological changes and capital formation. Finally, we constructed a new production function with data capital and other traditional factors of production and introduced standard household preferences to build an endogenous growth model. We proved that there existed a non-balanced steady state and examined its characteristics. Using different methods to input data capital and ICT capital into the production process avoided the usual problem of exaggerating the impact of ICT capital on economic growth, which occurred because ICT served both as capital and technology in the production function. We found that in the steady state of our growth model, data capital grew faster than other types of output. The steady-state aggregate growth rate of this model lay between traditional economic growth models without data capital and ICT capital, and economic growth models with only ICT capital. This theoretical finding was in line with recent empirical studies, suggesting that the traditional ICT model overestimated the impact of ICT capital on total factor production, resulting in inflated economic growth rate forecasts. We then estimated China’s stock of data capital, first using numerical simulation with our model and then using actual data. The results were similar, but the estimation based on real data was higher, which can be mostly explained by the difference in statistics and the fact that China’s economy is in transition and has not yet achieved a steady-state of capital accumulation. This paper made three policy recommendations. First, we strongly encourage bureaus of statistics to add data capital accounting to their digital economy accounting systems and to measure firms’ data capital by their actual cost. Second, to achieve the dual circulation of the Chinese economy, the Chinese government should construct more data capital infrastructure during its new infrastructure campaign, establish a well-functioning national data market, and strengthen cooperation with other economies on data capital transactions. Third, legislators should pay more attention to the property right protection of data capital, especially regarding the prevention of data abuse and securing the proper distribution of profits, which will significantly affect the economy’s growth potential in the long term.
Value production, value transfer and accumulation: a political economy analysis of uneven regional development in China
FENG Zhixuan;LI Bangxi;LONG Zhiming;ZHANG Chen
Economic Research Journal,2020,Vol 55,No. 10
This paper used a political economy approach to understand China’s uneven regional development in recent years. This paper summarized two theoretical frameworks related to the uneven regional development, the framework of production and the framework of exchange, and unified two seemingly contradictory theories, the labor theory of value and the capital circulation theory. Taking a static viewpoint, and using the labor theory of value, we explained that production and exchange frames can correspond to value production and value realization, respectively, which are the two main factors in the differences between regions in the value added per unit of labor time. To characterize dynamic processes, both frames introduce the capital accumulation process and use its interaction with production and exchange in the fields of technology and distribution. These two interactive processes can be unified in the logic of capital circulation, and the complex dynamics of uneven development between regions can be understood in this uniform framework. The relative magnitude of the cross-regional flow of value in the process of accumulation and the cross-regional transfer of value in the process of exchange embody the relative relationship between the two interactive processes. Based on these theories, this paper conducted an empirical study of the uneven development of regions in China. First, we divided GDP per capita into three factors: the value added per unit of working time, the average working time of workers, and the proportion of workers in the population. Furthermore, the difference in the value added per unit of labor time was decomposed into the production gap of the value per unit of labor time, the amount of transferred value per unit of labor time, and the differences in the value added rate expressed by the market price and individual labor time. Using national and provincial input-output data for 2002, 2007, and 2012, this paper calculated the gap in value production and the amount of transferred value in each provincial-level areas. We found that the gap in value production and the amount of transferred value are highly correlated with the GDP per capita between regions, and they can explain most of the inter-provincial differences in GDP per capita. Next, this paper analyzed the dynamic process of uneven development in China. On the basis of our theoretical framework, we introduced the net flow of value in circulation by subtracting the transfer of value in the process of exchange from the flow of value in the process of accumulation to examine the relative relationship between production and exchange. We identified a tendency to reduce regional differences in the interaction between accumulation and production processes, and we found that before 2007, the effect of this tendency was not sufficient to change the polarization effect in exchange. After 2007, the negative feedback of the accumulation and production processes gradually exceeded the positive feedback and weakened the polarization effect in the exchange process, resulting in a narrowing of the gap in development levels between the regions of China. We argued that the effect of balanced development will eventually overcome the effect of polarization because the process favors backward areas in China. Using the provincial panel data from 2001 to 2015 in China, we estimated the national Foley-Michl accumulation equation to explain why the accumulation process favors the backward regions. We found that the share of profits and the share of capital stock in the country—the two factors favoring developed regions—have short-term effects on capital accumulation but not long-term effects. The slow response of investment to capacity utilization also weakens its role in strengthening the accumulation level of developed regions. Although the ratio of potential output to capital promotes the accumulation of developed regions in the short term, it also has the larger effect of promoting the accumulation of backward areas in the long term. Therefore, in the long run, the entire accumulation system promotes capital accumulation in backward areas. This mechanism is a common consequence of the logic of the accumulation process and the shaping of the accumulation pattern by the government.
