Yu Yuxin and Wu Zhiyun

Shanghai International Studies University

Abstract: Interest rates are the key to the resource allocations of financial markets.The frequent appearance of negative nominal interest rates (NNIR) may lead to a failure of the transmission mechanism and arouse system risks in the financial markets.Meanwhile, negative nominal interest rates is a new policy with no consensus reached by academia or policymakers.It is necessary to review the research results and promote consensus to reveal the nature and impact mechanisms of NNIR.Therefore, we retrieved original articles from the Web of Science (WoS) and China National Knowledge Infrastructure (CNKI)published from 1999 to 2020 on NNIR to determine the characteristics of current research results from various perspectives and compare literature in English and Chinese of highly productive institutions and researchers, hot topics, evolution contexts, research frontiers, and ecological characteristics.There are three major findings.In terms of research ecology, the ecological structure of the top research institutions,both domestic and abroad, remains steady, but the structure of the researchers is not stable.In terms of a research domain, NNIR is studied from many dimensions, and the early established research domains still have long-lasting impacts in English literature.In contrast, Chinese literature mainly focuses on discussing applicable policies with no highly focused domain and research topic with great influence yet.Finally, the focus in both English and Chinese literature has changed.Since the original research framework is insufficient in explanatory power, literature in English is beginning to pay attention to the empirical analyses of practical policies, and Chinese scholars are turning to theoretical study to enhance the in-depth understanding of this phenomenon.Researchers in China should focus on collecting highquality research materials and pay more attention to the progress of empirical research in English literature to improve Chinese research efficiency and quality and then promote research progress in China.

Keywords: negative nominal interest rates (NNIR), bibliometrics, social network analysis, cluster analysis

Since the outbreak of the 2008 financial crisis, such developed countries as Denmark,Sweden, and Switzerland have successively implemented their negative nominal interest rate (NNIR) policies with profound influences.At present, the bonds issued with an NNIR have exceeded US20 trillion.Ministry of Finance of the People’s Republic of China issued four billion euro-denominated sovereign bonds on November 18 last year, of which the five-year 750 million euros first saw a negative interest rate with yields of -0.152 percent.This is the first time that China has issued NNIR treasury bonds.The appearance of relevant policies on NNIR and the existence of large-scale NNIR bonds have broken the cognitive framework of the original financial theories and the running logic of the current financial system, making it difficult to understand their real significance and potential impact.Concerns about the reality and confusion regarding the theory have led to the increased attention of researchers on the studies of NNIR.Because the financial system operates through adjusting the interest rate, i.e., the change of capital price, to guide the allocation of financial and other resources, the NNIR policy and treasury bonds may lead to systematic chaos on the price of the interest rate, the anchor of the financial system, and may even have a serious impact on the stability and effectiveness of the financial system.Although there are empirical studies conducted in the international academic circle and by decision makers in various countries on such questions as whether the NNIR is a trend inevitable, what risk may be faced by implementing the policies, where the effctive boundary of NNIR polies is, and what tools are included, there is still neither a clear theoretical framework nor a commonly agreed conclusion.This will bring great challenges to formulating and implementing monetary policy and financial risk management and control.It is necessary to conduct more and deeper research on NNIR to analyze it in a theoretical way.This will provide a reference for policy making and implementation in practice and meanwhile it will present theoretical support and policy tools to control financial and economic risks and maintain sustainable and stable development of the economy.

Relevant research on NNIR has been carried out in the academic circles, especially after the subprime mortgage crisis breaking out in some countries, which aroused more concerns over a wide range of topics and produced fruitful results.However, there is still little consensus, making it difficult to give a reasonable and holistic view on the topic through studying the literature due to such subjective factors as the authors’ capability, their value systems, and objective constraints on one’s time and energy.Moreover, it is not conducive to finding inter-related structures hidden in the literature nor promoting follow-up research in an in-depth way, or making full use of research resources.In this digital age, digital tools shall be adopted to systematically sort out the literature to present an overall view of the past and present studies and explore the latest discoveries.

Therefore, to facilitate the study in China, our study compares Chinese and English research results to reveal the differences in historical development, research topics, hot spots,and research frontiers.It is hoped that newcomers in this field can understand the overall research situation quicker and more systematically, improve research efficiency by finding potential research topics, important research authors, and key research documents, and finally, boost the study and improve its influence in China.

To systematically comb and comprehensively summarize the literature and promote the research of NNIR in China, we made full use of digital tools through CiteSpace visualization software to collect and analyze literature on NNIR research in the last two decades in the WoS and CNKI databases.We explored hot spots, evolution routes, and features of frontier research with the help of bibliometrics and social network analysis to systematically comb the existing achievements in this field and promote the depth of follow-up research in China.

Literature Review

As research papers increased explosively in recent years, traditional ways of reviewing the literature are being replaced with researchers using the inter-relationships formed between documents from a data mining perspective.Social network cluster analysis has been adopted and applied in multidisciplinary fields.Studies on environmental science, virology, botany,medicine, and pharmacy have widely adopted bibliometrics with significant achievements.

Wu et al.(2020) studied the distribution and migration of regional spatial heat by bibliometrics through Geographic Information System (GIS) spatial display and analysis and extracting relevant remote sensing data and regional information.Zhou et al.(2020) studied papers from CNKI and the WoS related to a cyanobacteria bloom to find the main reasons for the outbreak.Yang et al.(2021) used bibliometrics to make a statistical analysis of the publishing time, number of papers, authors, research institutions, etc., in the field of China’s public safety and put forward that the research in this field will turn to focus on urban public safety and health supervision systems.Guo et al.(2021) studied relevant literature on bioremediation of petroleum-contaminated soil from 1990 to 2019 from the core database of WoS and found that the future study will focus on the culture of high-efficiency petroleum hydrocarbon-degrading bacteria, the composition, and structure of microbial communities and joint application of bio-remediation, and other methods, which will ultimately lead to the transformation and application of bio-remediation results in engineering.Scholars in other countries have also obtained achievements through this method.Garousi et al.(2016) selected the most cited papers in software engineering (SE) using the Scoups database to present SE’s typical characteristics and research hotspots through bibliometrics and text mining.Najmi et al.(2017) employed bibliometrics to spot the turning point and new trends in transportation studies, including keyword cluster analysis, journal co-citations, and national cooperation.Curry et al.(2018) used bibliometrics to define the concept of new public management in terms of width and depth, which provides a deeper understanding for academia to participatein this topic.Yeo et al.(2020) conducted a detailed study on the research trend and cooperative network of perovskite solar cells through bibliometrics, which provided useful information to forecast future market demand for perovskite solar cells and next-generation solar photovoltaic panels.Rocchi et al.(2020) identified papers published in core journals, the authors, research institutions, countries, and research topics in agricultural systems through bibliometrics to understand related topics and current developments in alternative agricultural systems.

Bibliometrics is also widely used in natural science and in the study of economics and finance.Qiao et al.(2011) applied bibliometrics to make a statistical analysis of carbon finance based on data from journals of economy and management from CNKI.Bibliometrics was also used by Lin et al.(2011) to study papers on behavioral economics to provide suggestions for further development in this field.He et al.(2020) searched the literature on blockchain from the CNKI database and used bibliometrics to study the development of blockchain and real economic integration in China.Zhang et al.(2020) explained the relationship between the digital economy and other related concepts by using bibliometrics to analyze digital economy papers.Francesca B.& Caputo A.(2020) summarized the literature published in WoS from 1999 to 2018 on SMEs’ sustainable development and financial performance and identified authors, journals, and research topics with the greatest impact in the field and provided a comprehensive knowledge map.Goyal et al.(2020) focused on financial literacy and identified influential works through citation networks.Silvana et al.(2020) studied the current situation of social finance and banking and used bibliometrics to do quantitative and qualitative analysis of the papers to identify five theoretical topics.

Bibliometrics can enable researchers to summarize achievements in various fields efficiently and systematically.The method will promote discoveries and accelerate research development.Therefore, our research focused on and compared the Chinese and English research results on NNIR to find the potential connections hidden during the evolution of literature, the transformation of hot topic transformations, and potential topics at the research frontier, which will provide REFERENCES for future researchers.

Date and Methodology

To ensure high-quality analysis, we employed data from papers on NNIR as the keyword published in the core journals of the WoS and CNKI.WoS was established in 1900 and covers over 9300 journals worldwide (Zhang, 2020).It is an important database for obtaining global academic information and is widely recognized by the academic community for its authority and significance (Liao et al., 2020).CNKI, launched in 1988, is China’s largest and most authoritative academic journal database and covers over 80 percent of Chinese academic resources.Therefore, the literature retrieved from these two databases accuratelyreflect the development in this field, in both Chinese and English, in an all-around way.We also used CiteSpace to analyze Chinese and English literature.CiteSpace is a bibliometrics software based on co-citation theory and routing network algorithms by Chen Chaomei.Using bibliometrics in a specific research field can produce visual displays of the key path of the discipline in a visual form (Chen et al., 2015)

In WoS, we selected the core collection database.We searched the topic with “negative interest rate,” “zero interest rate,” or “zero lower bounds” in the subject field with “economics,”“business finance,” or “business,” and document type with “article.” We also searched the CNKI database subject field with “nominal negative interest rate,” “zero interest rate,” or“zero lower bound” from the core database, CSSCI, and CSCD.Although negative interest rate policies were not implemented before 2009, discussions on this topic were started much earlier.So, the time of literature retrieval was set from January 1, 1999, to December 31, 2020.We retrieved 1324 English papers and 354 Chinese papers.After manually deleting reviews,interviews, and repetitive papers, 1311 English and 270 Chinese papers were identified (see Table 1).

Table 1 Data Retrieval Method and Results

A Comparative Study on Achievements in Negative NNIR Published in Literature in English and Chinese

Number of Papers Published

Changes in the number of published articles can directly reflect how much concern was aroused on a specific subject during a certain period, which is important for forecasting the trend of the subject (Qiu, 2019) and a key indicator for understanding the progress in any specific field.The time curve of Chinese and English research results in this field is shown in Figure 1.It reveals that the literature in English continues to increase, especially after developed countries like Denmark and Sweden began to implement the NNIR policy after 2009.The research results were published at a rapid pace.With the outbreak of the COVID-19pandemic in 2020, the Federal Reserve set the benchmark interest rate at 0–0.25 percent, and the number of articles published in 2020 reached a historical peak.However, the publication of Chinese literature started relatively late, and the number of publications was far lower than that of English literature.Before 2009,there is only a few Chinese publications,and related research results started to grow significantly from 2011 to 2015.The number began to increase significantly only over the most recent five years, indicating that published research in Chinese lags far behind that published in English.This may be ascribed to the fact that Chinese bibliographic scholars and journals do not have a high sense of research in this field or that Chinese bibliographic scholars have limited research capabilities, resulting in fewer studies.

Figure 1 Comparison of the Number of Papers Published in Chinese and English Literature

Geographic Distribution

In the ranking of the number of published English-language literature, apart from China with 72 publications ranking sixth, the rest are all developed countries in Europe, America,and Japan.From the perspective of the centrality index, the influence of European countries, America, and Canada is much higher than that of other countries.The US takes the core position with the highest centrality value (0.6), with 490 papers, accounting for 37 percent of the published documents.The atlas of National Cooperation Networks (Figure 2)shows that only the US and the UK demonstrate more than 0.1 in centrality, reflecting their leading position as the two economic research powers in this field.By referring to Table 2,we can see the positioning of European countries and the US that started to turn to this field as early as the turn of the new century, with correspondingly greater influence.Although Chinese scholars published 72 articles, the earliest was published in 2001.The centrality is only 0.01, covering only about 5 percent of the achievements of French scholars with 67 papers published.This shows that publications on NNIR in Chinese production are not small in numbersbut low in impact.Much remains to be done to improve the quality and impact of Chinese research in this field.

Figure 2 Atlas of National Cooperation Networks listing NNIR Research

Table 2 Ranking List of Countries Publishing Papers on NNIR (According to number of papers)

Journal Distribution

Analyzing the sources of articles can provide an understanding of the distribution of achievements in a specific discipline across different core journals.Literature in English on NNIR was distributed in 536 journals, while literature in Chinese was found in less than 100.Tables 3 and 4 show the distribution of the top five journals in Chinese and English over the 20-year period and the 3-year period, respectively.The number of the top five journals in English accounts for 23.87 percent of the total literature in the 20-year period and 16.95 percent in the 3-year period.It shows that the number of related journals increased faster as more research results were published, indicating that more attention to the topic was paid by scholars in this field.The number of articles published in the top five Chinese journals accounted for 31.85 percent in the 20-year measured period and increased to 41.80 percent during the 3-year measured period.The concentration of journals with the relevant publications grew significantly, but unfortunately, journals likeChina Finance, with low impact, account for a much higher proportion than publications in high-impact journals, indicating that not much attention has been given to this subject.Preliminary research results may also be one of the reasons.The distribution of journals in Table 3 and 4 also shows that the number and distribution of articles in English journals are more stable.And some journals have a long-term focus on this area, while the distribution of Chinese journals shows that only a few journals are focusing on this area, and the mainstream academic journals with greater influence basically do not focus on this area, which may be related to the low quality of research results in Chinese literature and also has some reference for researchers to submit papers.The distribution of Chinese journals shows that only a few journals are focusing on this area.

Table 3 Journal Distribution on Research on NNIR (1999-2020)

Table 4 Journal Distribution on Research on NNIR (2018-2020)

Institutional Distributions

From the distribution of research institutions (Table 5 lists the top five institutions over the 20-year period, and Table 6 shows the top five institutions over the 3-year period).The data indicate that research institutions publishing English papers focus on policy and decision-making research,such as the Federal Reserve System, followed by the National Bureau of Economic Research.The proportion of articles published by these institutions has not changed much, as shown in Tables 5 and 6, indicating that American policy decision-making research institutions pay close attention to NNIR and have conducted comprehensive and systematic research.The People’s Bank of China tops the Chinese list during this period, indicating that the decision-making institutions in China also show a strong interest in this.However, the proportion of papers published by People’s Bank of China in recent years published in recent years has declined, ranking behind the Chinese Academy of Social Sciences and Renmin University of China, which shows that China’s decisionmaking institutions have relatively few public research results.This may be ascribed to China’s low demand for a negative interest rate policy.Overall, the top five research institutions in both English and Chinese are relatively stable.However, the stability of Chinese research institutionsis largely because most of the results have only appeared in the last three years.China still needs time to verify whether the research of these institutions will continue to advance in the future.This also indicates that the ecology of negative interest rate research in Chinese literature is not yet mature.

Table 5 Distribution of Research Institutions on NNIR (1999-2020)

Table 6 Distribution of Research Institutions on NNIR (2018-2020)

Author Distributions

Analysis of the cooperative network of authors can indicate the core author groups and their cooperative relations.Figure 3 shows a pooled analysis of the authors of the sample literature.In terms of the number fo papers published, there are small teams with two or three members in both English and Chinese literature, indicating that although there is some cooperation among scholars, the research teams are small in number.It is worth noting that the authors with high productivity and high total citation frequency, such as Eggertsson G.and Pan Chengfu, only have a limited scope of research cooperation.This implies that the cooperation between core authors is not extensive and that much remains to be done.

Figure 3 Atlas of Author Cooperative Networks on NNIR Research in English and Chinese Literature

Table 7 and Table 8 sort out the top ten authors who have published papers over the past 20-year and 3-year periods, respectively.From the perspective of the author’s working institutions,research on NNIR, as a new frontier with a high demand for theoretical innovation and discussion,mainly depends on universities and research institutes.Although the previous data show that decision-making institutions ranked high in the number of published articles, universities are still the main power from the perspective of knowledge-creating value.Geographically, the high-yield authors mainly come from the US, and there are no more than two from Sweden, Japan, Germany,and other countries.According to citation frequency, the most highly cited authors, Eggertsson and Gbillir, come from the US.The research progress in this field is dominated by scholars from Europe and America, especially the former, which is consistent with the overall state of economic research.

Table 7 Authors on NNIR in English and Chinese Literature (1999-2020)

Table 8 Authors on NNIR in English and Chinese Literature (2018-2020)

Eggertsson G.from Princeton University published many papers and is cited frequently in both the 20-year and 3-year periods.This is mainly because his paper, “The zero bound on interest rates and optimal monetary policy,” published in 2003, established an inter-temporal dynamic equilibrium model to explore the optimal monetary policy framework under the constraint of a zero interest rate.This paper is of pioneering significance with many citations.

The related research in Chinese starts relatively late.The most cited article in the past 20 years is Pan Chengfu’s “Theory, Practice, and Impact of Quantitative Easing of Monetary Policy” in theStudy of International Financein 2009.However, the paper that has received the most attention in recent years should be Ma Li’s “Research on Macro Policy Transmission Based on Zero Lower Bound of Interest Rate Constraints,” published in the mainstream journalEconomic Researchin 2015.This article uses mathematical modeling, impulse response, etc., to start from the two situations of zero interest rate lower bound constraints and no zero interest rate lower bound constraints to conduct a comparative study on the implementation effect of the macro-controlsystem composed of monetary policy and fiscal policy.It is a theoretical article on the dynamic stochastic general equilibrium (GSGE) model, including the zero-interest rate lower bound constraint.Subsequent domestic scholars have widely cited the reference provided by the research.Ma Li published related results one after another, becoming the scholar who published the most Chinese literature.

It should be pointed out that there have been significant changes in the names and rankings of authors in the past 20 years and the past 3 years, except for a few authors.This indicates that the research ecosystem of authors has not yet stabilized.Moreover, the total citation ratio of the top 10 authors in English literature in the recent 3-year period is 13.5 percent, lower than the total citation ratio of 20.45 percent in the 20-year period, showing rapid progress towards a stable research ecology.However, the literature in Chinese paints another picture.In the 3-year period, the top 10 authors have often been cited, accounting for 64 percent with a high degree of centrality.This is because Chinese literature has only been widely published recently, and significant research findings are relatively limited.It further shows that the related research of Chinese literature is insufficient, and it is urgent to build a stable ecology.

A Comparative Study on Research Topics

Research Subject

Keywords of a paper, as a generalization of the research subject by scholars, can often reflect the research scope, key topics, and research focus of an article.There may be many keywords in a paper, and the paper links them together.Social network analysis can help establish the co-occurrence relationships between keywords, and reveal the relationships between different topics.Through cluster analysis, we identified the links between topics from the objective relationships within the data.Our goal was to find the relationships between hot topics in this field and their evolutionary routes while at the same time showing the development of recent research frontiers.

With the help of CiteSpace, we made a co-occurrence analysis of the keywords used in Chinese and English literature.The network map of Chinese and English literature research on NNIR, with the network node set as “keywords” and the time node set as one year, is shown in Figure 4.The color and thickness of the growth rings indicate the time keywords first appearedand their number.The size of nodes indicates the frequency of keywords, and the color of the connection between nodes indicates the earliest time when two keywords appeared together.The thickness of the connecting lines indicates the co-occurrences between keywords.The keywords with high frequency and high intermediary in literature in English mainly include “interest rate,”“model,” “term structure,” “monetary policy,” and “currency.” These keywords build a relatively independent cluster, which shows that the research topics are diversified and focus on theory and policy.At the same time, literature in Chinese takes the keyword “monetary policy” as the core.Moreover, the keywords with high frequency and high intermediary include “zero interest rate,”“l(fā)iquidity trap,” “Federal Reserve,” “monetary policy,” “interest rate policy,” and “quantitative easing,” which show that Chinese literature mainly focuses on policy with preliminary discussions related to theory.

Figure 4 Keywords Co-occurrence Atlas of Papers on NNIR in English and Chinese

The keywords with high centrality were sorted out (Table 9) based on the keyword cooccurrence atlas, and we found obvious differences between Chinese and English literature in this field.

Table 9 A Comparison of High-frequency Keywords in Papers on NNIR in English and Chinese (According to centrality)

Literature in English is diversified in research topics.Moreover, the objectives focus on policy and inflation and discussions based on the zero-interest model.Considering the failures of price mechanisms and monetary policies, quantitative easing and fiscal policy have also become a focus.In addition to studies on policies, literature in English also discusses such theoretical issues as the liquidity trap.Because this is a brand-new economic issue, the high-frequency cooccurrence of the keywords “risk,” “debt,” and “uncertainty” shows that “risk” is also the focus of research.In comparison, there are fewer hot topics and a relatively narrow research perspective in Chinese literature.Chinese researchers are more inclined to investigate foreign policies and economies with such keywords as “policy effect,” “impact and response,” “developed economies,”“European Central Bank,” and “Japan.” It shows that Chinese literature mainly focuses on the analysis of sensible policies or the evolution of policies with a preliminary study on theory.

The Methods Are Different

The appearance of the keywords “model,” “l(fā)iquidity,” and “inflation” shows that the authors of literature in English focus on the study of economic models and in-depth theoretical discussions of negative interest rates.Chinese literature researchers are good at summarizing reality and specific policies and use event study methods to analyze the impact of specific policies with more empirical research than theoretical research.

The Geographic Areas Are Different

Literature in English covers a wide range of developed and emerging economies in the Eurozone,Japan, the US, and other regions or countries.Studies on NNIR for Chinese literature have just started, and the theoretical research is insufficient.Also, the research mainly focuses on empirical and theoretical studies of the reasons for low-interest rates and the effects of negative interest rate policy in Japan.

Topic Centrality

To further study the relationships between the topics in the literature, the keywords are summarized through clustering of co-occurrence networks to reflect the development of the main research fields.This paper extracted the literature keywords in the 20-year period to form a cooccurrence map, and a spectral clustering algorithm generated the topic cluster.Compared with the traditional algorithm, the spectral clustering algorithm can identify the clustering of samples with arbitrary shapes and spaces, converging to a holistic optimal solution.Extracting the label keywords after clustering could reveal the research field related to the topics.Specifically, the CiteSpace tool is used to form the cluster atlas of Figure 5 (the top 10 clusters).Its automaticclustering tag can connect them according to keyword similarity based on a default view, showing the distribution of research in this field from different angles.Higher clustering means a larger scope of the clustering topic and a greater number of published papers.

Figure 5 Comparison of keywords clustering on NNIR Literature in English and Chinese

The keywords clustering atlas of literature in English shows 0.3046 in modularity value with an average silhouette value of 0.9153, indicating the network community is clear in structure and fine in clustering.At the same time, the atlas of literature in Chinese shows 0.4129 in modularity value with an average silhouette value of 0.9421.This demonstrates that the community structure of the cluster atlas of Chinese literature research is more significant than that of English literature, which may be related to the late start of Chinese literature research with limited perspectives.It can also be seen from Figure 4 that literature in English is of higher overlapping clustering among various categories, which shows that the correlation between different topics is closer, and that the research in related fields is deeper.Literature in Chinese demonstrates greater differences in clustering with scattered topics, and much remains to be done in the field.

Finally the last day of school arrived and the elf was free to go. As for homework, there was no more, so he quietly and slyly slipped out the back door.

The top ten keywords in Chinese and English in terms of clustering scale can be seen in Table 10.The results show that except for the “l(fā)iquidity trap,” there are great differences in clarification between English and Chinese literature.Keywords in papers in English include many different perspectives on NNIR.It shows that they have done systematic and in-depth studies, while Chinese research mainly focuses on policy-related keywords.Literature in Chinese still lags behind that in English, which may be related to the lack of accumulation of Chinese research.This also means that Chinese literature has more room for improvement in the future, and young scholars have more opportunities in this field.

Table 10 Comparison of Keywords Clustering on NNIR Literature in English and Chinese

Topic Timeline

To understand the context and trends of the research topic, a timeline knowledge map wasdrawn by CiteSpace to reveal the evolution of NNIR research.From top to bottom, the timeline view shows that the cluster scale decreases, although the larger the cluster scale, the more important the cluster field is.From left to right, the time for citing is indicated.The time span and evolution map of each clustered document can be observed through connecting lines.

The timeline of keyword clustering in English literature on NNIR is shown in Figure 6.It is significant that the subjects formed in the early stage show greater impact, a longer lasting time,and are closely related to each other.However, recently, the number of topics with great impact has decreased significantly, showing that the research on negative interest rates has fallen into the original framework and failed to break through, or there is not much prospect in this field.Currently, failure to break through is the more likely condition, i.e., constrained in the original framework with insufficient understanding of the problem, leading to a lack of a main theme.Thus, there is an urgent need for new theoretical breakthroughs to stimulate additional research in this field, hopefully, to achieve greater progress.Regarding constant research, cluster #1 banking,and #2 liquidity trap top the list.Studies related to these subjects have been published throughout the 20-year period.This is because the impact of negative interest rates is mainly on the current financial system, especially the banking system.Negative interest rates will lead to the failure of financial price information, making liquidity traps inevitable.Therefore, virtually all research will have some relationship with these two topics.

Furthermore, the #4 model and #5 zero lower bound are regularly discussed.This is because many theoretical frameworks in English literature are based on the DSGE model,with zero interest rate used as the research benchmark.Judging from the size of the clustering nodes, before 2010, large nodes appeared in the English literature research, indicating that landmark literature, i.e., highly cited with a strong intermediary nature, had been published,and these papers impacted the entire trend.This shows strong accumulation in this field.In recent years, concerns about the research clustering #3 fiscal policy, #6 quantitative easing, and#8 macroeconomic variables have also increased.The keywords with high frequency mainly include central bank independence, macroeconomic variables, inflation expectations, and VAR, which are closely related to the policies of various developed countries to deal with the subprime mortgage crisis.Moreover, the negative interest rate policy has been implemented in a few countries, and researchers following this topic could study the real impacts of relevant policies as they evolved in real time.

The impact of topics in recent years is far less than that in earlier times, but the number of papers published is much greater.However, based on the English literature, there is little indication that a consensus on the subject has been reached, nor have new influential topics appeared.It seems much remains to be done for further development.More empirical results are needed that can lead to theoretical breakthroughs and form new research topics with a common focus.

As shown in Figure 7, the timeline of keyword clustering in Chinese literature indicates thatthere are only a few influential topics except for the two topics of “zero interest rate” and “monetary policy,” which obviously contrasts with the diversified topics of English literature.Among the top ten clusters, only the first two clusters show the longest-lasting time (cluster # 0 interest rate policy and # 1 zero interest rate), while the other eight clusters are different.Among them, cluster# 6 bond market was the last to appear, and no influential paper has been published on the topic.The Chinese literature shows low centrality and no clear research topic with great influence.The influence of the topic list is fragmented, showing that the ecology of Chinese research in this field is far from being formed.

Figure 7 Timeline of keywords clustering of literature in English and Chinese on NNIR

Analysis of the NNIR Research Frontier

The burst value in CiteSpace software is used to characterize the sudden appearance of a certain keyword.The higher the burst value of a keyword in a specific period, the more it indicates that the term is a hot spot of academic research in a specific period (Wang & Chu, 2015).The results of keyword burst values for NNIR in Chinese and English literature during our study are shown in Table 11.

Table 11 Burst Values of Keywords in English and Chinese Literature in NNIR (1999-2020)

Overall, the burst keywords in English literature show a longer lasting time than those in Chinese literature.This indicates that English researchers have been focusing on the topic longer.Such hot topics as “l(fā)iquidity trap,” “zero bound,” and “interest rate risk” have been studied for as long as seven years with great impact.It is worth noting that these words appeared earlier, which shows that early scholars’ research on negative interest rates was mostly theoretical.Only in recent years have they begun to pay attention to empirical research.

In Chinese literature, “interest rate,” “policy effect,” and “quantitative easing” are keywords that have had the longest influence, some as long as four years, showing that the academic discussions in Chinese literature were mainly policy-oriented in the early stages with less theoretical discussions on negative interest rates.The emergence of the DSGE model in recent years shows that the discussion of Chinese literature is mainly within the theoretical framework of English literature.While more countries have started to issue NNIR bonds and implement relevant policies, the discussions on the real results of NNIR are increasing.Chinese scholars’research on negative interest rates is going from empirical to theoretical, while scholars writing in English are changing from theoretical to empirical research on the impact of policies.The research in Chinese literature lags far behind the research in English literature.Much remains to be done if China is to gain the momentum to grasp the potential effects of NNIR policies truly.

Conclusion and Enlightenment

Conclusion

Based on bibliometrics, we retrieved data from WoS and CNKI.We compared the Chinese and English literature on NNIR from the number of papers published, the distribution of journals,institutions, and authors, the research topics, and research frontiers.The following conclusions were made:

First, in terms of literature distribution, there are obvious differences between Chinese and English literature from the dimensions of regional publications, periodicals, research institutions, and authors.From the perspective of geographical distributions, developed countries such as members of the EU and the US, especially the US, take the core position and dominate the research in this field.China’s research achievements and influence in this field need to be improved.From the distribution of published journals, the literature on English NNIR research comes from a wide range of journals.In recent years, the increasing number of related journals of published papers indicates that this research field has attracted increased attention.However, the distribution of Chinese journals shows that the mainstream academic journals with great influence pay less attention to it.From the perspective of the distribution of research institutions, American policy decision-making research institutions pay close attention to the NNIR and conduct comprehensive and systematic studies.The top five research institutions in both English and Chinese studies are relatively stable.The ecology of English research shows certain stability, while Chinese research institutions are weak in stability because most of the achievements have appeared recently, which also shows that the research ecology of Chinese research in this field is not yet mature and has significant room for development.From the point of view of author distributions, in the recent 20-year and 3-year periods covered by our study, the ranking of cited authors in both English and Chinese indicatesthat the ecological structure of the author’s research is not yet stable.It is worth noting that the proportion of the top ten authors cited in English literature in the recent 3-year period is far lower than that in the recent 20-year period, indicating that this field has made rapid progress and has not yet formed a stable structure of research author ecology.However, the situation of Chinese literature is just the opposite.In the recent 3-year period, the top ten authors have a high concentration, because the Chinese literature has mainly been published in the recent 3-year period, and the number of research results is limited.It further shows that Chinese-related research is weak, and the ecological needs of research authors are urgent.

Second, there are significant differences between Chinese and English literature from the perspective of research hotspots.From the perspective of the differences between Chinese and English research topics, the research objects of English literature not only explore the policy,but also discuss theoretical issues such as liquidity traps.Because this is a new economic problem, its potential risks have become the focus of attention of English literature researchers.In contrast, Chinese literature is more about discussing sensible policies.From the perspective of clustering, the overlapping degree of English literature clustering is high, and because the clustering difference of Chinese literature is large, it indicates that the correlation between different categories of English literature research topics is high.The research on Chinese literature correlation is still in a scattered stage, and all aspects need to be further discussed.In addition, the main keywords in English include different dimensions of the impact of nominal negative interest rates, which shows that its research has systematic and in-depth characteristics.The research in Chinese literature mainly focuses on policy-related keywords, which reflects the lack of adequate participation in Chinese literature research and many realistic discussions.From the perspective of the research topic timeline, English literature has had a great influence on the early formation of topic fields.From the topic line of research topics, the English literature is more influential in the areas formed in the early years and lasted longer with more intensive interconnections, while the topics with greater influence on the recent past are obviously scarece, indicating that the research on negative interest rate has failed to form a breakthrough under the original theoretical framework and the research consensus is far from being reached.The research focus of Chinese literature is not high, and there is no clear research topic with great influence.The scattered influence of topic lists shows that the Chinese research ecology in this field is far from mature.

Third, from the perspective of research frontiers and trends, the emphasis on Chinese and English literature is different.The research frontiers of English literature are beginning to focus on practical policies, while Chinese literature is beginnings to turn towards theoretical study.This is because English literature research must break the existing theoretical research boundaries through empirical research results.However, the policy of Chinese literature lacks depth, and it is necessary to improve the research results and deepen the cognition in this field through in-depth theoretical research for future scholars.English literature should contribute to empirical research results, and Chinese literature should pay attention to the contribution of theoretical research results.

Enlightenment

Through the analysis in this paper, here is the enlightenment drawn in this field:

First, there is still no consensus achieved in the field, which shows a lot of research space and opportunities yet to be explored.Both English and Chinese literature in this field have been stuck in a bottleneck, with no clear consensus reached yet.However, NNIR applications may develop very quickly, so we recommend that researchers in China choose research topics from their fields of expertise.They can then pay close attention to the empirical research in English literature and theoretical research in Chinese literature to produce more high-quality results.

Second, theoretical research can be strengthened.The obvious deficiency is that the theoretical research in China is weak, and the in-depth discussion of the problem mechanism is insufficient,leaving much room to be improved.Learning from foreign theoretical research results and combining this knowledge with empirical research is a great opportunity to produce high-quality research results.

Third, at present, attention should be paid to the collection of foreign research data because it is more systematic and in-depth.High-quality research results are based on good basic materials.English literature research in this field is more systematic, so we can collect high research documents according to the key authors of English literature research as determined in this paper and use new digital tools such as ChatGPT to help obtain and refine data and improve research efficiency.

Fourth, enhance domestic research and strive for the recognition of authoritative journals.Compared with English literature, Chinese literature has fewer authoritative journals, and mainstream journals pay less attention to this field.It is necessary to improve the research results and demonstrate its practical value to attract more outstanding researchers with the recognition of more mainstream authoritative academic journals.Searching for or developing more excellent researchers could help promote the formation and development of research ecology in this field.